papers-we-love_papers-we-love/nautilus.db

SQLite format 3

@  C<00>
C-<2D>
<0F>
<0E><0F><0E>
r<0C>
IV,+

<00>p
<01>?tablelinkslinksCREATE TABLE links
  (id integer primary key,
   paper_id int,
   url varchar unique not null,
   title varchar not null,
   directory varchar not null,
   status int not null,
   created varchar,
   modified varchar))=
indexsqlite_autoindex_links_1links
<0A>|	
<01>Wtablefilesfiles
CREATE TABLE files
  (id integer primary key,
   paper_id int,
   sha1 varchar unique not null,
   filename varchar not null,
   directory varchar not null,
   normalized varchar not null,
   created varchar,
   modified varchar))
=
indexsqlite_autoindex_files_1files<0B>
!!
<01>etabletagspaperstagspapers	CREATE TABLE tagspapers
  (id integer primary key,
   tag_id integer not null,
   paper_id integer not null)a
<01>%tabletagstagsCREATE TABLE tags
  (id integer primary key,
   tag varchar unique not null)';
indexsqlite_autoindex_tags_1tags<08>''
<01>qtableauthorspapersauthorspapersCREATE TABLE authorspapers
  (id integer primary key,
   author_id integer not null,
   paper_id integer not null)<29>0
<01>7tableauthorsauthorsCREATE TABLE authors
  (id integer primary key,
   name varchar unique not null,
   first_name varchar,
   middle_name varchar,
   last_name varchar)-A
indexsqlite_autoindex_authors_1authors<05>\

<01>tablepaperspapersCREATE TABLE papers
  (id integer primary key,
   title varchar unique not null,
   year int,
   abstract varchar,
   venue varchar,
   directory varchar,
   created varchar,
   modified varchar)+?
indexsqlite_autoindex_papers_1papers<00><0C><00><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>~ytoje`[VQLGB=71+%

<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>}wqke_YSMGA;5/)#
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
{
u
o
i
c
]
W
Q
K
E
?
9
3
-
'
!



	
<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C> with Epicc: An Essential Step Towards Holistic Security Analysis<07>Many threats present in smartphones are the result of interactions between application components, not just ar-tifacts of single components. However, current techniques for identifying inter-application communication are ad hoc and do not scale to large numbers of applications. In this paper, we reduce the discovery of inter-component communication (ICC) in smartphones to an instance of the Interprocedural Distributive Environment (IDE) problem, and develop a sound static analysis technique targeted to the Android platform. We apply this analysis to 1,200 applications selected from the Play store and characterize the locations and substance of their ICC. Experiments show that full specifications for ICC can be identified for over 93% of ICC locations for the applications studied. Further the analysis scales well; analysis of each application took on average 113 seconds to complete. Epicc, the resulting tool, finds ICC vulnerabilities with far fewer false positives than the next best tool. In this way, we develop a scalable vehicle to extend current security analysis to entire collections of applications as well as the interfaces they export.android/2017-09-11T23:06:19.5280620122017-09-11T23:06:19.528062012<EFBFBD><00>g<02>=GGFlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps<07>Today's smartphones are a ubiquitous source of private and confidential data. At the same time, smartphone users are plagued by carelessly programmed apps that leak important data by accident, and by malicious apps that exploit their given privileges to copy such data intentionally. While existing static taint-analysis approaches have the potential of detecting such data leaks ahead of time, all approaches for Android use a number of coarse-grain approximations that can yield high numbers of missed leaks and false alarms.
 In this work we thus present FlowDroid, a novel and highly precise static taint analysis for Android applications. A precise model of Android's lifecycle allows the analysis to properly handle callbacks invoked by the Android framework, while context, flow, field and object-sensitivity allows the analysis to reduce the number of false alarms. Novel on-demand algorithms help FlowDroid maintain high efficiency and precision at the same time.
 We also propose DroidBench, an open test suite for evaluating the effectiveness and accuracy of taint-analysis tools specifically for Android apps. As we show through a set of experiments using SecuriBench Micro, DroidBench, and a set of well-known Android test applications, FlowDroid finds a very high fraction of data leaks while keeping the rate of false positives low. On DroidBench, FlowDroid achieves 93% recall and 86% precision, greatly outperforming the commercial tools IBM AppScan Source and Fortify SCA. FlowDroid successfully finds leaks in a subset of 500 apps from<00><><00><><00><><00><><00><>
<00><><00><>
<00><><00><><00><><00><><00><>{<00><>y<00><>w<00><>u<00><>s<00><>rނq܂mۂiقd؂aׂ`ւ]ԂZӂX҂WтSЂQςO΂M͂ÎG˂DȂBǂ?Ƃ=Ă9Â8‚7<00><>6<00><>4<00><>2<00><>/<00><>+<00><>(<00><>%<00><>"<00><><00><><00><><00><><00><><00><><00><><00><><00><>	<00><><00><>
<00><><00><>}<00><>|<00><>y<00><>u<00><>s<00><>r<00><>n<00><>k<00><>f<00><>d<00><>b<00><>`<00><>^<00><>\<00><>X<00><>U<00><>S<00><>P<00><>L<00><>I<00><>F<00><>D<00><>A<00><>=<00><>;<00><>8<00><>6<>5~<7E>0}<7D>-|<7C>){<7B>#z<>!y<>x<>w<>v<>u<>t<>q<>o<>n<>
l<>k<>j<>
ih|gydvcsbpam]jZgYbX`W\VYUVTSSPQMJJIEHCE?D<C8B4A1@-=)<%;":987654321<0E>^<00><0E>T^<0E><0F>A
<0A>
@
<01>
<EFBFBD><06><0C>
<0A><07><04>
<01>P<08><05>!<0E>I<02><03>@W<03><04>"<07>A<00>{/<0B><06>O	l<0C><00>*<02>D
"
1	D
+	<09>o<08><07> <00><0F><0B>
<0A><05>
<01>
T|~<06>Xx<0B><06>*Y
RRB-Trees: Efficient Immutable VectorsI#K
Immutability Changes EverythingH0e
Mathematical Aspects of Consciousness TheoryG!
NTRU PrimeF"I
New directions in cryptographyE-_
The Moral Character of Cryptographic WorkD9
Acoustic CryptanalysisC3
Crash-Only SoftwareBC
Attacks on the WEP protocolAV<04>/
Simple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithms@K<04>
A Method for Obtaining Digital Signatures and Public-Key Cryptosystems?E<04>

Time, Clocks, and the Ordering of Events in a Distributed System>0e
Microreboot - A Technique for Cheap Recovery=2i
Experience with Processes and Monitors in Mesa<
Hol;-_
Message Analysis for Concurrent Languages:7s
The semantics of x86-CC multiprocessor machine code9@<04>
Finding race conditions in Erlang with QuickCheck and PULSE8F<04>
Heap architectures for concurrent languages using message passing7V<04>/
Everything you always wanted to know about synchronization but were afraid to ask67s
Panorama weaving: fast and flexible seam processing57s
High-quality single-shot capture of facial geometry4<}
Coupled 3D reconstruction of sparse facial hair and skin3$M
Procedural modeling of buildings29w
Imaging vector fields using line integral convolution15
Instant architecture0N<04>
Shape Grammars and the Generative Specification of Painting and Sculpture/<}
Diminished reality for augmented reality interior design.!
PushPull++-C
Interactive Horizon Mapping,,]
Light Propagation Volumes in Cryengine 3+)
The Redox Code*/
Blue native PAGE.)9
The rendering equation(4m
Web page classification: Features and algorithms'Z<04>7
KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera&/
Deep Colorization%<}
3-Sweep: extracting editable objects from a single photo$"I
Poisson surface reconstruction#0e
Illumination for Computer Generated Pictures")W
Continuous Shading of Curved Surfaces!5o
An improved illumination model for shaded display P<04>#
GigaVoxels: ray-guided streaming for efficient and detailed voxel renderingP<04>#
Digital Video Stabilization and Rolling Shutter Correction using GyroscopesJ<04>
Piranha: A scalable architecture based on single-chip multiprocessing'S
Object Space Silhouette AlgorithimsH<04>
MEXICA: A computer model of a cognitive account of creative writingA<04>
A program optimization for automatic database result caching3k
On the resemblance and containment of documentsJ<04>
On computable numbers with an application to the EntscheidungsproblemP<04>#
2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm'S
A DNA-Based Archival Storage System,]
BIG Cache Abstraction for Cache Networks'S
The chemical basis of morphogenesisB<04>
Molecular computation of solutions to combinatorial problems.A
Interactive topic modeling1g
VEWS: A Wikipedia Vandal Early Warning System/c
Safety Verification of Deep Neural Networks@<04>
The BUDS Language for Distributed Bayesian Machine Learning4m
Evaluating Generative Models for Text Generation+[
The algorithmization of counterfactuals
*Y
Causal Diagrams for Empirical Research"I
A Theory of Inferred CausationG<04>
Mastering the game of Go with deep neural networks and tree search
P<04>#
Architectural Styles and the Design of Network-based Software Architectures	-_
Security Concerns in Android mHealth Apps(U
Computing Machinery and Intelligence8u
Analyzing inter-application communication in AndroidC
Direct and Indirect Effects|<04>{
Analysis of Three Bayesip0e
Illumination for Computer Generated Pictures"<00>Z<04>5Making lockless synchronization fast: performance implications of memory reclamation<00>I	L<04>
K/Axodraw Version 2<00><00>._Programming Languages: History and Future<00>2i
ExpL[<04>9
Don't settle for eventual: scalable causal consistency for wide-area storage with COPST<00>G<04>The Derivative of a Regular Type is its Type of One-Hole Contexts<00>
<0F><00><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>
<0A>
<0A>
<0A>
o
R
-
<0C><0C><0C>qX0<0B><0B><0B>b-
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
e
7
	<09>	<09>	<09>	<09>	_	>	<08><08><08><08>n@)<07><07><07><07>W0<06><06><06><06>{X5<05><05><05><05>jD)<04><04><04>sT7<03><03><03><03>uR+<02><02><02>vQ2
<01>
<01>
<01>
<01>
e
L
+
<00>!p)
Otmar HilligesOtmarHilligeso
David KimDavidKimn'
Shahram IzadiShahramIzadim
Bin ShengBinSheng!l)
Qingxiong YangQingxiongYangk%
Zezhou ChengZezhouCheng#j+
Daniel Cohen-OrDanielCohen-Ori!
Shi-Min HuShi-MinHuh%
Ariel ShamirArielShamirg
Zhe ZhuZheZhuf
Tao ChenTaoChene%
Hugues HoppeHuguesHoppe#d+
Matthew BolithoMatthewBolitho(c1Michael M. KazhdanMichaelM.Kazhdan"b+Bui Tuong PhongBuiTuongPhonga'
Henri GouraudHenriGouraud!`)
Turner WhittedTurnerWhitted!_)
Elmar EisemannElmarEisemann%^-
Sylvain LefebvreSylvainLefebvre!])
Fabrice NeyretFabriceNeyret\'
Cyril CrassinCyrilCrassin[#
Salim VirjiSalimVirjiZ!
Marc LevoyMarcLevoyY%
Jongmin BaekJongminBaekX%
David JacobsDavidJacobs)W1
Alexandre KarpenkoAlexandreKarpenkoV#
Bruce GoochBruceGoochU%
Elaine CohenElaineCohenT%
Mark HartnerMarkHartner!S)
Ashley HartnerAshleyHartnerR'
Mike SharplesMikeSharples0Q9Rafael Pérez Y PérezRafaelPérez YPérezP'
Adam ChlipalaAdamChlipalaO!
Ziv ScullyZivScully$N-Andrei Z. BroderAndreiZ.BroderM'
Dennis ShashaDennisShasha%L-
Theodore JohnsonTheodoreJohnsonK'
Karin StraussKarinStraussJ%
Georg SeeligGeorgSeeligI
Luis CezeLuisCeze(H1Douglas M. CarmeanDouglasM.Carmean!G)
Randolph LopezRandolphLopez!F)
James BornholtJamesBornholtE!
Gong ZhangGongZhangD
Runhui LiRunhuiLiC%
Zhi-Li ZhangZhi-LiZhang%B-
Arvind NarayananArvindNarayananA%
Eman RamadanEmanRamadan@#L M AdlemanLMAdleman%?-
Brianna SatinoffBriannaSatinoff.>7#Jordan L. Boyd-GraberJordanL.Boyd-Graber=!
Yuening HuYueningHu(<1%V. S. SubrahmanianV.S.Subrahmanian);1
Francesca SpezzanoFrancescaSpezzano:%
Srijan KumarSrijanKumar9
Min WuMinWu8
Sen WangSenWang,75#Marta Z. KwiatkowskaMartaZ.Kwiatkowska6'
Xiaowei HuangXiaoweiHuang!5)
Chris JermaineChrisJermaine*43Luis Leopoldo PerezLuisLeopoldoPerez3#
Shangyu LuoShangyuLuo2%Zekai J. GaoZekaiJ.Gao#1+
Suvrat BhooshanSuvratBhooshan0'
Raunaq RewariRaunaqRewari%/-
Prasad KawthekarPrasadKawthekar.%
Thomas VermaThomasVerma!-)
Demis HassabisDemisHassabis,'
Thore GraepelThoreGraepel'+/
#Koray KavukcuogluKorayKavukcuoglu#*+
Madeleine LeachMadeleineLeach,)5Timothy P. LillicrapTimothyP.Lillicrap!()
Ilya SutskeverIlyaSutskever%'-
%Nal KalchbrennerNalKalchbrenner&
John NhamJohnNham%'
Dominik GreweDominikGrewe#$+
Sander DielemanSanderDieleman#%
Marc LanctotMarcLanctot3";
)Vedavyas PanneershelvamVedavyasPanneershelvam)!1
!Ioannis AntonoglouIoannisAntonoglou- 5
'Julian SchrittwieserJulianSchrittwieser4=George Van Den DriesscheGeorgeVan DenDriessche'
Laurent SifreLaurentSifre#
Arthur GuezArthurGuez&/Chris J. MaddisonChrisJ.Maddison
Aja HuangAjaHuang%
David SilverDavidSilver(1David S. RosenblumDavidS.Rosenblum*3Roy Thomas FieldingRoyThomasFielding#+
Klara NahrstedtKlaraNahrstedt )Carl A. GunterCarlA.Gunter#+
Muhammad NaveedMuhammadNaveed#
Dongjing HeDongjingHe%A. M. TuringA.M.Turing"+David A. WagnerDavidA.Wagner!)
Kate GreenwoodKateGreenwood,5Adrienne Porter FeltAdriennePorterFelt!
Erika ChinErikaChin%-
Rusmin SoetjiptoRusminSoetjipto
#Rose F. LiuRoseF.Liu!
Somesh JhaSomeshJha%-
Patrick McdanielPatrickMcdaniel*
3Patrick D. McdanielPatrickD.Mcdaniel	'
Damien OcteauDamienOcteau'Yves Le TraonYvesLeTraon'
Jacques KleinJacquesKlein%-
Alexandre BartelAlexandreBartel#
Eric BoddenEricBodden#+
Christian FritzChristianFritz+3
Siegfried Rasthofe<00><>M<00><>J<00><>C݈C<00><>B<00><>X<00><>n<00><>m<>^<5E>0R<>G?<3F>Z>p{2<00><0F><0F>2<0F><0F>eG<0F>!tM
<01>
<0A>
<EFBFBD>	<09><07><04><05><06><04>2	<09><08>Hb
<0A><0B><0F>	'Z*<0E>3	i<07><07><06><0C>
9
(<0E>
<EFBFBD>P	<09><08><0F><0E>	<0B><05>
r <05>
<0A><04>
<EFBFBD>
<01>m<06><06><08><06>w<06><0C>
{~<02>
<EFBFBD><05><06>t<03><02><03>
	XG<0F>
<0A>n
`<0E>N<03>o<03><0C>"
<0A>k
<01>3
<EFBFBD><0C><02>
N	I	<09><04>4<0B><08>E<08><05><03>	<09><0B>u
<03><07>B-<04>%#[d<07>1	<09>
<EFBFBD>R<07><02>_<04>
<01>6
<EFBFBD><0E>	9
:<05><02><0B><07>>	<0F>X<0B>c<04><0F>7><08>j!
K\<02>y<0C><0C><02>G<08>JpX
_<05><0B>a
<01>l-^
<EFBFBD>
!Adi Shamir<00>-Ronald L. Rivest<00>)Leslie Lamport<00>#Armando Fox<00>'Greg Friedman<00>'Yuichi Fujiki<00>/Shinichi Kawamoto<00>'George Candea<00>+David D. Redell<00>/Butler W. Lampson<00>!Rob Arthan<00>%Konrad Slind<00>'John Harrison<00>-Richard Carlsson<00>%Jade Alglave<00>-Magnus O. Myreen<00>+Thomas Braibant<00>Tom Ridge<00>#Scott Owens<00>=Francesco Zappa Nardelli<00>%Peter Sewell<00>'Susmit Sarkar<00>%Ulf T. Wiger<00>#Thomas Arts<00>'Hans Svensson<00>#John Hughes<00>1Nicholas Smallbone<00>+Michal H. Palka<00>'Koen Claessen<00>1Jesper Wilhelmsson<00>5Konstantinos Sagonas<00>)Erik Johansson<00>5Vasileios Trigonakis<00>-Rachid Guerraoui<00>#Tudor David<00>-Valerio Pascucci<00>'Julien Tierny<00>#Brian Summa<00>!Bob Sumner<00>+Markus H. Gross<00>-Robert W. Sumner<00>+Steve Marschner<00>/Paul A. Beardsley<00>-Gioacchino Noris<00>%Bernd Bickel<00>%Thabo Beeler<00>%Luc Van Gool<00>'Andreas Ulmer<00>'Simon Haegler<00>1Leith Casey Leedom<00>%Brian Cabral<00>-William Ribarsky<00>5François X. Sillion<00>)Michael Wimmer<00>!James Gips<00>%George Stiny<00>)Sanni Siltanen<00>)Pascal Müller<00>#Peter Wonka<00>#Markus Lipp<00>-Michael F. Cohen<00>3Peter-Pike J. Sloan<00>+Anton Kaplanyan<00>#Helmut Sies<00>'
Dean P. Jones/
Hermann Schägger~-
Hans-Peter Braun}#
Ilka Wittig|+
James T. Kajiya{-
Brian D. Davisonz%
Xiaoguang Qiy5
Andrew W. Fitzgibbonx/
Andrew J. Davisonw)
Dustin Freemanv%
Steve Hodgesu'
Jamie Shottont)
Pushmeet Kohlis3
Richard A. Newcomber+
David Molyneauxq)
Otmar Hilligesp

David Kimo'
Shahram Izadin

Bin Shengm)
Qingxiong Yangl%
Zezhou Chengk+
Daniel Cohen-Orj!
Shi-Min Hui%
Ariel Shamirh
Zhe Zhug
Tao Chenf%
Hugues Hoppee+
Matthew Bolithod1
Michael M. Kazhdanc+
Bui Tuong Phongb'
Henri Gourauda)
Turner Whitted`)
Elmar Eisemann_-
Sylvain Lefebvre^)
Fabrice Neyret]'
Cyril Crassin\#
Salim Virji[!
Marc LevoyZ%
Jongmin BaekY%
David JacobsX1
Alexandre KarpenkoW#
Bruce GoochV%
Elaine CohenU%
Mark HartnerT)
Ashley HartnerS'
Mike SharplesR9
Rafael Pérez Y PérezQ'
Adam ChlipalaP!
Ziv ScullyO-
Andrei Z. BroderN'
Dennis ShashaM-
Theodore JohnsonL'
Karin StraussK%
Georg SeeligJ

Luis CezeI1
Douglas M. CarmeanH)
Randolph LopezG)
James BornholtF!
Gong ZhangE

Runhui LiD%
Zhi-Li ZhangC-
Arvind NarayananB%
Eman RamadanA#
L M Adleman@-
Brianna Satinoff?7
Jordan L. Boyd-Graber>!
Yuening Hu=1
V. S. Subrahmanian<1
Francesca Spezzano;%
Srijan Kumar:

Min Wu9
Sen Wang85
Marta Z. Kwiatkowska7'
Xiaowei Huang6)
Chris Jermaine53
Luis Leopoldo Perez4#
Shangyu Luo3%
Zekai J. Gao2+
Suvrat Bhooshan1'
Raunaq Rewari0-
Prasad Kawthekar/%
Thomas Verma.)
Demis Hassabis-'
Thore Graepel,/
Koray Kavukcuoglu++
Madeleine Leach*5
Timothy P. Lillicrap))
Ilya Sutskever(-
Nal Kalchbrenner'

John Nham&'
Dominik Grewe%+
Sander Dieleman$%
Marc Lanctot#;
Vedavyas Panneershelvam"1
Ioannis Antonoglou!5
Julian Schrittwieser =
George Van Den Driessche'
Laurent Sifre#
Arthur Guez/
Chris J. Maddison

Aja Huang%
David Silver1
David S. Rosenblum3
Roy Thomas Fielding+
Klara Nahrstedt)
Carl A. Gunter+
Muhammad Naveed#
Dongjing He%
A. M. Turing+
David A. Wagner)
Kate Greenwood5
Adrienne Porter Felt!
Erika Chin-
Rusmin Soetjipto#
Rose F. Liu
!
Somesh Jha-
Pf#H. I. SerinG<00>5Robert Bruce Findler5<00>!N. Machida<04>#Erik MeiG%Dhiru Kholia<02>F)Boris Dragovic[<00>)Luis Rodriguez<02><00>)Jacob R. Lorch
<01><00>T. Marmon/<0F><00><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>zrjc[SKC;3+#<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>{skd\UNF>6.&
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
~
v
n
f
^
V
N
F
>
6
.
&



<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>~vnf^VNF>6.&<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>wmcYOE;1'	
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
}
s
i
_
U
K
A
7
-
#


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	y	o	e	[	Q	G	=	3	)				
<08><08><08><08><08><08><08><08><08><08><08><08>ukaWMC9/%<07><07><07><07><07><07><07><07><07><07><07><07><07>{qg]SI?5+!
<06><06><06><06><06><06><06><06><06><06><06><06><06>wmcYOE;1'	<05><05><05><05><05><05><05><05><05><05><05><05><05>}si_UKA7-#<04><04><04><04><04><04><04><04><04><04><04><04><04>yoe[QG=3)<03><03><03><03><03><03><03><03><03><03><03><03><03>vlbXND:0&<02><02><02><02><07>k

Ji<07>j

Ii<07>i

Hi<07>h

Gi<07>g

Fi<07>f

Ei<07>e

Dh<07>d

Ch<07>c

Bh<07>b

Ah<07>a

9h<07>`

@g<07>_

?g<07>^

>g<07>]

=f<07>\

<f<07>[

;f<07>Z

:f<07>Y

9f<07>X

8f<07>W

7f<07>V

6f<07>U

5f<07>T

4f<07>S

3f<07>R

2f<07>Q
<00>f<07>P

1f<07>O

0e<07>N

/e<06>M

Md<07>L

.d<07>K
<00>d<07>J

-d<07>I

,c<07>H

+c<07>G

*c<07>F

)c<07>E

(c<07>D

'b<07>C

&a<07>B

%a<07>A

$a<07>@

#a<07>?

"a<07>>

!`<07>=

 _<07><

_<07>;

^<07>:

^<07>9

^<07>8

^<07>7

]<07>6

]<07>5

]<07>4

]<07>3

\<07>2

\<07>1

\<07>0

\<07>/

\<07>.

\<07>-

\<07>,

\<07>+

\<07>*


Z<07>)

Z<07>(

Z<07>'


Z<07>&

	Y<07>%

Y<07>$

Y<07>#

X<07>"

X<07>!

X<07> 

X<07>

X<07>


X<07>

X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>X<07>
<00>W<07>
<00>W<07>
<00>V<07>
<00>U<07>
<00>U<07>
<00>U<07>
<00>U<07>
<00>U<07>

<00>U<07>
<00>U<07>
<00>T<07>

<00>T<07>	
<00>T<07>
<00>T<07>
<00>S<07>
<00>S<07>
<00>S<07>
<00>S<07>
<00>R<07>
<00>R<07>

<00>R<07>
<00>Q<07>
<00>Q<07>~
<00>O<07>}
<00>O<07>|
<00>N<07>{
<00>N<07>z
<00>N<07>y
<00>N<07>x
<00>N<07>w
<00>N<07>v
<00>M<07>u
<00>M<07>t
<00>M<07>s
<00>M<07>r
<00>M<07>q
<00>M<07>p
<00>M<07>o
<00>M<07>n
<00>M<07>m
<00>M<07>l
<00>M<07>k
<00>L<07>j
<00>K<07>i
<00>K<07>h
<00>K<07>g
<00>J<07>f
<00>J<07>e
<00>I<07>d
<00>I<07>c
<00>H<07>b
<00>G<07>a
<00>F<07>`
<00>F<07>_
<00>F<07>^
<00>F<07>]
<00>E<07>\
<00>E<07>[
<00>D<07>Z
<00>C<07>Y
<00>C<07>X
<00>C<07>W
<00>B<07>V
<00>B<07>U
<00>A<07>T
<00>@<07>S
<00>@<07>R
<00>?<07>Q
<00>?<07>P
<00>?<07>O
<00>><07>N
<00>=<07>M
<00>=<07>L
<00>=<07>K
<00>=<07>J
<00>=<07>I
<00><<07>H
<00><<07>G
<00>;<07>F
<00>;<07>E
<00>;<07>D
<00>:<07>C
<00>:<07>B
<00>:<07>A
<00>9<07>@
<00>9<07>?
<00>9<07>>
<00>9<07>=
<00>9<07><
<00>9<07>;
<00>9<07>:
<00>9<07>9
<00>8<07>8
<00>8<07>7
<00>8<07>6
<00>8<07>5
<00>8<07>4
<00>8<07>3
<00>8<07>2
<00>7<07>1
<00>7<07>0
<00>7<07>/
<00>6<07>.
<00>6<07>-
<00>6<07>,
<00>5<07>+
<00>5<07>*
<00>5<07>)
<00>4<07>(
<00>4<07>'
<00>4<07>&
<00>4<07>%
<00>4<07>$
<00>3<07>#
<00>3<07>"
<00>3<07>!
<00>3<07> 
<00>3<07>
<00>3<07>
<00>3<07>
<00>2<07>
<00>2<07>
<00>2<07>
<00>2<07>
<00>2<07>
<00>1<07>
<00>1<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>/<07>
<00>/<07>
<00>.<07>
<00>-<07>
<00>-<07>

<00>-<07>
<00>,<07>
<00>,<07>

<00>+<07>	
<00>*<06>

*<06>

~)<06>

})<06>

|)<06>

{(<06>

z'<06>

y'<06>


x&<06>

w&

v&~

u&}

t&|

s&{

r&z

q&y

p&x

o&w

n&v

m%u

l%t

k%s

j$r

i$q

h$p

g$o

f$n

e#m

d#l

c#k

b"j

a!i

` h

_g

^f

]e

\d

[c

Zb

Ya

X`

W_

V^

U]

T\

S[

RZ

QY

PX

OW

NV

MU

LT

KS

JR

IQ

HP

GO

FN

EM

DL

CK

BJ

AI

@H

?G

>F

=E

<D

;C

:B

9A

8@

7?

6>

5=

4<

3;

2:

19

08

/7	

6	
5

.4	
3

-
2

,
1

+
0

*
/

)
.

(
-

'
,

&
+

%
*

$
)

#
(

"
'

!
&

 
%


$


#


"


!


 




	

	

















	




















	



	

	







<00><>ZɊ <00><>f`<60>,_<>k<0F><00><0F><0F><0F><0F><0F><0F>sj^L<$<0E><0E><0E><0E><0E><0E><0E><0E>{ogZPB9 
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
t
c
Q
B
6
(
 

<0C><0C><0C><0C><0C><0C><0C><0C>s[K80(
<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>|tl\PH4(	

<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
}
q
h
\
N
C
7
'


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	q	b	M	@	/	<08><08><08><08><08><08><08>k\?6+<07><07><07><07><07><07><07><07><07><07><07>q_@7'<06><06><06><06><06><06><06><06><06><06>\L-$<05><05><05><05><05><05><05>{eN6<04><04><04><04><04><04><04><04>ypg\PG:1(<03><03><03><03><03><03>|laOE<0
<02><02><02><02><02><02><02><02><02><02>^TG3'
<01>
<0A>q!hash table<0F>p%immutability<07>orime	<09>nripemd<11>m)future attacks
<EFBFBD>lupgrade<07>kblem<1F>jEdiffie-hellman key agreement<06>idlp
<0A>h!public-key<0B>gknapsack
<0A>f!disclosure<07>etalk	<09>dpuzzle<0F>c%cryptography<10>b'cryptographer	<09>areboot<0C>`expensive<08>_crash<15>^1persistent storage	<09>]uptime<06>\wep<07>[read<0F>Z%plementation<08>Yqueue
<0A>X!concurrent<0F>W%non-blocking<1A>V;public-key cryptosystem<11>U)decryption key<06>Tecc<12>S+electronic mail<11>R)encryption key<14>Q/key cryptosystems<06>Pdsa<14>O/encryption method<06>Ntes<06>Mdes
<EFBFBD>Llogical<06>Kdis	<09>Jcausal<08>Iclock<06>Hpen<06>Grus<07>Ffine<0E>E#microreboot<06>Dbug<15>C1priority inversion<0C>Boperating<08>Ainter<14>@/personal computer<0B>?handling<19>>9concurrent programming
<EFBFBD>=monitor<16><3memory architecture<15>;1garbage collection<14>:/allocation scheme<13>9-machine language<12>8+actual hardware<0F>7%memory model<06>6hol<10>5'correct model	<09>4erlang<15>31concurrent program<0F>2%unit testing<11>1)race condition<08>0pulse<0E>/#concurrency<06>.mcs<1C>-?synchronization primitive
<0A>,!contention$<24>+Operformance and energy efficiency<07>*lock	<09>)mosaic<0B>(panorama<07>'seam
<EFBFBD>&editing	<09>%stereo<06>$dif	<09>#facial<1B>"=reconstruction algorithm<0F>!%skin surface<0B> scanning<07>hair
<0A>!cityengine<06>cga<1C>?line integral convolution<0F>%vector field
<0A>!streamline<06>eld<06>odt
<EFBFBD>grammar<08>split<06>mar	<09>street	<09>facade	<09>carbon<07>nadp<11>)ros production<07>nadh<08>nadph<0B>
radiance<0F>%illumination<08>tance<06>
ray<1A>	;document classification<0C>hypertext<1A>;web page classification<16>3text classification<0B>relevant<07>tsdf<0C>depth map<14>/3d reconstruction<19>
9kinectfusion algorithm<1A>;deep learning technique1reference database~%colorization}cylinder|-simple 3d shapes
{!photographz%single photo
yfittingxpmvwrbfvureu9poisson reconstructiontmvsslightingrbrdfqspecular
pshadingo#reflectancenture	mshadow	lviewerk#ray tracing
jgraphic	ishaderhrendering
grealismfgpus
eoctreesdstreamingcgpubvoxelamate`gyroscope
_shutter^'camera motion]3video stabilization
\writing	[mexicaZcbrY)computer model
Xtension
WminhashV+minwise hashingUlsh
TshingleS#resemblanceRlfuQlirPlrfuOarcNacmM%data storageL'biotechnologyKarchivalJencoding
IblockinH-hamiltonian pathGhppF'dna computing
Egraph g
D!same topicCldaBitmA)topic modeling@#topic model?3vandalism detection>'early warning=edit	<vandal;9comfort and confidence:)counterfactual9-little knowledge8swiftness	7enigma6-bayesian network5causality4dag3sgs2causation
1alphago
0!board game/'reinforcement.%intelligence
-!artificial,soap+=rest architectural style	*cation)api(soa
'mhealth&)sensitive data%hipaa$5security and privacy#judge"bot!los 5machine intelligencecentprivilegedroidcomdroidcde
naturalndedoxmediationdata flow
!smartphone)essential step3market applications7n.a. n.a. pc analysis	intenticc/security analysis3android application
#android app'analysis tool
malware
leak	flowdroidappowslifecycle%bp algorithm+message passing+graphical model%facto<00><>z<00><>'r<>=P<>ZO<>q<0F><0F><00><0F><0F><0F><0F><0F>%
<0A><0F><0B><0B>
u<0C><0F><0B>U<0B>
C<0F>	<09><04>
<EFBFBD><07>
<0A>Q

)h:8(]	0[<0C>
m<05><04>M<05><0C><02><02>	A
<0E><0B><03><08><08>2<06>_H<02><02><0B>@<0E>Q	t<03><0C><06><07><03><0B><03><0C><05><0E><02><07><06><0F>z	<09>t47
<EFBFBD>
i<07>
8<0F>
<EFBFBD><0B><04>
<01>
<0A><05><0B>]
d<0E><04>1<03><08><02>)km<0F>	<09>Au<0C><06>;}I!f_<07><0E>
<EFBFBD>%<0E><05><0F>
<EFBFBD>
<0A><04>)5<06>	<09><0E><07><07>
p|}
r<07><04><0F><06>h]<04>	cP	<09>	<09><04>C<02><03>	<02>b<05>7
(	<09>F
]<02><06>		<09>
R<08>
O]
<0A>(<07>q<06>
<0A>
<0A>
!
D	<09>
Q
<EFBFBD>	N	r<06><0E>
<0A>
<0A>	<09><07><06>
~r<07><0C>.<02>,)<08>L9<08>
	<05>H1	<09><0C>\`
<EFBFBD>

<EFBFBD>l=
<EFBFBD>!hash table<00>%immutability<00>	rime<00>ripemd<00>)future attacks<00>upgrade<00>	blem<00>!Ediffie-hellman key agreement<00>dlp<00>!public-key<00>
knapsack<00>!disclosure<00>	talk<00>puzzle<00>%cryptography<00>'cryptographer<00>reboot<00>expensive<00>
crash<00>1persistent storage<00>uptime<00>wep<00>	read<00>%plementation<00>
queue<00>!concurrent<00>%non-blocking<00>;public-key cryptosystem<00>)decryption key<00>ecc<00>+electronic mail<00>)encryption key<00>/key cryptosystems<00>dsa<00>/encryption method<00>tes<00>des<00>logical<00>dis<00>causal<00>
clock<00>pen<00>rus<00>	fine<00>#microreboot<00>bug<00>1priority inversion<00>operating<00>
inter<00>/personal computer<00>
handling<00>9concurrent programming<00>monitor<00>3memory architecture<00>1garbage collection<00>/allocation scheme<00>-machine language<00>+actual hardware<00>%memory model<00>hol<00>'correct model<00>erlang<00>1concurrent program<00>%unit testing<00>)race condition<00>
pulse<00>#concurrency<00>mcs<00>?synchronization primitive<00>!contention<00>&Operformance and energy efficiency<00>	lock<00>mosaic<00>
panorama<00>	seam<00>editing<00>stereo<00>dif<00>facial<00>=reconstruction algorithm<00>%skin surface<00>
scanning<00>	hair<00>!cityengine<00>cga<00>?line integral convolution<00>%vector field<00>!streamline<00>eld<00>odt<00>grammar<00>
split<00>mar<00>street<00>facade<00>carbon<00>	nadp<00>)ros production<00>	nadh<00>
nadph<00>
radiance<00>%illumination<00>
tance<00>ray<00>;document classification<00>hypertext<00>;web page classification<00>3text classification<00>
relevant<00>	tsdf<00>depth map<00>/3d reconstruction<00>9kinectfusion algorithm<00>;deep learning technique<00>1
reference database%
colorization~
cylinder}-
simple 3d shapes|!
photograph{%
single photoz
fittingy
pmvx
rbfw
urev9
poisson reconstructionu
mvst
lightings
brdfr
specularq
shadingp#
reflectanceo
turen

shadowm

viewerl#
ray tracingk
graphicj

shaderi

renderingh
realismg
gpusf
octreese

streamingd
gpuc	
voxelb
matea

gyroscope`
shutter_'
camera motion^3
video stabilization]
writing\

mexica[
cbrZ)
computer modelY
tensionX
minhashW+
minwise hashingV
lshU
shingleT#
resemblanceS
lfuR
lirQ
lrfuP
arcO
acmN%
data storageM'
biotechnologyL
archivalK
encodingJ
blockinI-
hamiltonian pathH
hppG'
dna computingF
graph gE!
same topicD
ldaC
itmB)
topic modelingA#
topic model@3
vandalism detection?'
early warning>
edit=

vandal<9
comfort and confidence;)
counterfactual:-
little knowledge9

swiftness8

enigma7-
bayesian network6

causality5
dag4
sgs3

causation2
alphago1!
board game0'
reinforcement/%
intelligence.!
artificial-
soap,=
rest architectural style+

cation*
api)
soa(
mhealth')
sensitive data&	
hipaa%5
security and privacy$	
judge#
bot"
los!5
machine intelligence 
cent

privilege	
droid
comdroid
cde
natural
nde
dox

mediation

data flow!
smartphone)
essential step3
market applications7
n.a. n.a. pc analysis

intent
icc/
security analysis3
android application#
android app
'
analysis tool
malware
leak


N Cimplementation osmcs<00><00>
paxos
9M)crash-recovery<03><00>/
security analysisN%global state<03><0F><00><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>~vnf^VNF>6.&<0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E><0E>~vnf^VNF>6.&
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
~
v
n
f
^
V
N
F
>
6
.
&



<0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C><0C>~vnf^VNF>6.&<0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B><0B>}sj`VLB8.$
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
z
p
f
\
R
H
>
4
*
 


	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	<09>	w	m	c	Y	O	E	;	2	(			
	<08><08><08><08><08><08><08><08><08><08><08><08>ukaWMC9/%<07><07><07><07><07><07><07><07><07><07><07><07><07>{qg]SI?5+!
<06><06><06><06><06><06><06><06><06><06><06><06><06>wmcYOE;1'	<05><05><05><05><05><05><05><05><05><05><05><05><05>}si_UKA7-#<04><04><04><04><04><04><04><04><04><04><04><04><04>yoe[QG=3)
<03><03><03><03><03><03><03><03><03><03><03><03>ukaWMC9/%<02><02><02><02><07>k

Gc<07>j

Fc<07>i

Eb<07>h

Db<07>g

Cb<07>f

Bb<07>e

Ab<07>d

@b<07>c

?b<07>b

>b<07>a

=b<07>`

<a<07>_

;a<07>^

:a<07>]

9a<07>\

8a<07>[

7_<07>Z

6_<07>Y

_<07>X

5_<07>W

4_<07>V

3^<07>U

2^<07>T

1^<07>S

0^<07>R

^<07>Q

]<07>P

/]<07>O

.]<07>N

-]<07>M

,]<07>L

+\<07>K
<00>\<07>J

*\<07>I

)Z<07>H

(Z<07>G

'Z<07>F

&Z<07>E

%Z<07>D

$Y<07>C

#Y<07>B

"Y<07>A

!Y<07>@

 Y<07>?

X<07>>

X<07>=

X<07><
<00>X<07>;

X<07>:

W<07>9

W<07>8

W<07>7
<00>W<07>6

W<07>5

U<07>4

U<07>3

U<07>2

U<07>1

U<07>0

S<07>/

S<07>.

S<07>-

S<07>,

S<07>+
<00>R<07>*

R<07>)
<00>R<07>(
<00>R<07>'
<00>R<07>&


Q<07>%

Q<07>$

Q<07>#


Q<07>"

	Q<07>!

O<07> 

O<07>
<00>O<07>
<00>O<07>
<00>O<07>

N<07>

N<07>

N<07>

N<07>
<00>N<07>

N<07>


N<07>

N<07>
<00>N<07>
<00>N<07>
<00>M<07>
<00>L<07>
<00>L<07>
<00>L<07>
<00>L<07>

<00>L<07>
<00>K<07>
<00>K<07>

<00>K<07>	
<00>K<07>
<00>K<07>
<00>J<07>
<00>J<07>
<00>J<07>
<00>J<07>
<00>J<07>
<00>H<07>

<00>F<07>
<00>F<07>
<00>F<07>~
<00>F<07>}
<00>F<07>|
<00>E<07>{
<00>E<07>z
<00>E<07>y
<00>E<07>x
<00>E<07>w
<00>D<07>v
<00>D<07>u
<00>D<07>t
<00>D<07>s
<00>D<07>r
<00>B<07>q
<00>B<07>p
<00>B<07>o
<00>B<07>n
<00>B<07>m
<00>A<07>l
<00>@<07>k
<00>@<07>j
<00>@<07>i
<00>@<07>h
<00>@<07>g
<00>?<07>f
<00>?<07>e
<00>?<07>d
<00>?<07>c
<00>?<07>b
<00>?<07>a
<00>?<07>`
<00>?<07>_
<00>?<07>^
<00>?<07>]
<00>><07>\
<00>><07>[
<00>><07>Z
<00>><07>Y
<00>><07>X
<00>=<07>W
<00>=<07>V
<00>=<06>U

v=<07>T
<00>=<07>S
<00><<07>R
<00><<07>Q
<00><<07>P
<00><<07>O
<00><<07>N
<00><<07>M
<00><<07>L
<00><<07>K
<00><<07>J
<00>:<06>I

:<07>H
<00>:<07>G
<00>:<07>F
<00>:<07>E
<00>9<07>D
<00>9<07>C
<00>9<07>B
<00>9<07>A
<00>9<07>@
<00>8<07>?
<00>8<07>>
<00>8<07>=
<00>8<07><
<00>8<07>;
<00>7<06>:

7<07>9
<00>6<07>8
<00>6<07>7
<00>6<07>6
<00>6<07>5
<00>6<07>4
<00>5<07>3
<00>5<07>2
<00>5<07>1
<00>5<07>0
<00>4<07>/
<00>4<07>.
<00>4<07>-
<00>4<07>,
<00>4<07>+
<00>3<07>*
<00>3<07>)
<00>3<07>(
<00>3<07>'
<00>2<07>&
<00>2<07>%
<00>2<07>$
<00>2<07>#
<00>2<07>"
<00>1<07>!
<00>1<07> 
<00>1<07>
<00>1<07>
<00>1<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>0<07>
<00>*<07>
<00>*<07>
<00>*<07>
<00>*<07>
<00>*<07>
<00>(<07>
<00>(<07>
<00>(<06>

r(<07>
<00>(<07>
<00>'<07>

<00>'<07>
<00>'<07>
<00>'<07>

<00>'<07>	
<00>&<07>
<00>&<07>
<00>&<07>
<00>&<06>

c&<07>
<00>%<06>

%<06>

~%<06>


}$<06>

|$

{$~

z$}

y$|

x#{

w#z

v#y

u#x

t#w

s"v

r"u

q"t

p"s

o"r

n q

m p

l o

k n

j m

i l

h k

g j

fi

eh

dg

cf

be

ad

`c

_b

^a

]`

\_

[^

Z]

Y\

X[

WZ

VY

UX

TW

SV

RU

QT

PS

OR

NQ

MP

LO

KN

JM

IL

HK

GJ

FI

EH

DG

CF

BE

AD

@C

?B

>A

=@

<?

;
>

:
=

9
<

8
;

7
:

69

58

47

36

25

1
4

0
3

/
2

.
1

-
0

,	/

+	.

*	-

)	,

(	+

'*

)

&(

%'

$&

#%

"$

!#

 "

!

 

















































	

	






	<00><>$<00><>j\<5C>/[<5B>k<0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F>
<01><00><00>]<5D>+1<>#GG78c295cfd7469cd3d494a48df7bd7748139e0660digital_video_stabilization_and_rolling_shutter_correction_using_gyroscopes.pdfcomputer_graphics/digital video stabilization and rolling shutter correction using gyroscopes2017-09-11T23:06:05.6673129882017-09-11T23:06:05.667312988<EFBFBD>]<5D>#3<>GG30fae8663ffba4f4abca068a9bc8735a590a9bc5A framework for automated generation of questions across formal domains.pdfcomputer_education/a framework for automated generation of questions across formal domains2017-09-11T23:06:05.6346818852017-09-11T23:06:05.634681885<EFBFBD>]<5D>?<3F>GGce8411564f95396b503868217469e2aaf1b996c9mexica-a-computer-model-of-a-cognitive-account-of-creativing-writing.pdfcomputational_creativity/mexica a computer model of a cognitive account of creativing writing2017-09-11T23:06:05.5951909182017-09-11T23:06:05.595190918<EFBFBD>
]<5D>Q{GG83cf2b3372ef98f7fa5caf94aa44e7262ee47519story-of-squeak-a-practical-smalltalk-written-in-itself.pdfcomp_sci_fundamentals_and_history/story of squeak a practical smalltalk written in itself2017-09-11T23:06:05.4806750492017-09-11T23:06:05.480675049<EFBFBD>5]<5D>9Q<39>1EE7edaa9cc255ba8e0938cb563110b204a4f393d60recursive-functions-of-symbolic-expressions-and-their-computation-by-machine-parti.pdfcomp_sci_fundamentals_and_history/recursive functions of symbolic expressions and their computation by machine parti2017-09-11T23:06:05.475392092017-09-11T23:06:05.47539209<EFBFBD>Q	]UQMGG1c1ff93040a96dfe9f1309bfe34a989d5f93bb4fhints-for-computer-system-design.pdfcomp_sci_fundamentals_and_history/hints for computer system design2017-09-11T23:06:05.4713090822017-09-11T23:06:05.471309082<EFBFBD>
]<5D>	Q<>
GGfb2db075fa0230289a4f05caf2127b95fcc9aa9cearly-lisp-history-1956-1959-herbert-stoyan-html-rendering.pdfcomp_sci_fundamentals_and_history/early lisp history 1956 1959 herbert stoyan html rendering2017-09-11T23:06:05.3734951172017-09-11T23:06:05.373495117<EFBFBD>Y		]]QUGG4712e0a50083a6bda848bf4a65fe214f0f6a7069axiomatic-basis-computer-programming.pdfcomp_sci_fundamentals_and_history/axiomatic basis computer programming2017-09-11T23:06:05.3045129392017-09-11T23:06:05.304512939<EFBFBD>q]<5D>
<1D>GG6e39523a0acd9855ff465598253c323f7dfd3cdaa-program-optimization-for-automatic-database-result-caching.pdfcaching/a program optimization for automatic database result caching2017-09-11T23:06:05.2589628912017-09-11T23:06:05.258962891<EFBFBD>]<5D><1D>GG6718cc5cd4e1484990ee79a8c3cffaad6d7271c3a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdfcaching/a constant algorithm for implementing the lfu cache eviction scheme2017-09-11T23:06:05.2532370612017-09-11T23:06:05.253237061<EFBFBD>
]<5D>)<1D>!GGd62de5f995164fff50f5ce61c0113f6bc9f042252q-a-low-overhead-high-performance-buffer-management-replacement-algorithm.pdfcaching/2q a low overhead high performance buffer management replacement algorithm2017-09-11T23:06:05.2014589842017-09-11T23:06:05.201458984<EFBFBD>8	]O+GGGe76af50e96b12fc507e73b025fe9da4a99600af9shazam-audio-search-algorithm.pdfaudio_comp_sci/shazam audio search algorithm2017-09-11T23:06:05.1690869142017-09-11T23:06:05.169086914<EFBFBD>h	]+wGG3a05eea36ffdbcf0625d5154a6458e75ca835971an-ethnographic-and-technological-study-of-breakbeats.pdfaudio_comp_sci/an ethnographic and technological study of breakbeats2017-09-11T23:06:04.4569431152017-09-11T23:06:04.456943115<EFBFBD>]<5D>=<3D>GG02cc6a5944d57d2353a55639c7b77336b94f29b6efficient-selectivity-and-backup-operators-in-monte-carlo-tree-search.pdfartificial_intelligence/efficient selectivity and backup operators in monte carlo tree search2017-09-11T23:06:04.4221010742017-09-11T23:06:04.422101074<EFBFBD>S	]a=YGGac14e6bf50d1491043baf1d854727a68f5f3f51d3-bayesian-network-inference-algorithm.pdfartificial_intelligence/3 bayesian network inference algorithm2017-09-11T23:06:04.4156010742017-09-11T23:06:04.415601074<EFBFBD>
	])#!EEbd9e0c2f5aaf68d784862ab361cc1a41fc9b32cdapi-design.pdfapi_design/ap<19>%><00><>/<18><17>w<00>g[M2"<0F><0F><0F><0C><0C>r<0B>YVd
=<0B><02>
<06><03>	<09>
^<02>g<08>M7
<01><00><07>l:<0B>
	<09><05>o
<07>
<EFBFBD>K<06>
<0E><0E><00>u<05>
1<03>
<0A>
<0A>	&)	<09>E<02><03>
<01>
<EFBFBD>P<0F><08><0F>x}
a
<0A><0E>H<05>
<EFBFBD><07> 
4<08><06>
j	S
<01>B<04>?<04>#,]
763d0321ced31b774bd4ba2f9f369c087cbd278eW,]
43c7b3780b5864f99d042392d83ab331f7fddf2aV,]
4bf4acf54bfd2e65b1ed31fe272670a7e276c534U,]
1a0ba12427c68642a4871677b9de7a337356b9f6T,]
f16c6ce0c7eabd4f5896962335879b3932138e52S,]
a2e4dc4b1cce765255e4d15084811da125c564c5R,]
3e375c8d996b8c46c83b9d3f72732d7477e5fd86Q,]
f3050b5586ddfec5da0d719338a6afa8b166985bP,]
c20baa16cb57ff4979569871d15294fa720bbc23O,]
57efc2b9ba2a725af1d66cc43c472d0314190051N,]
bde7543a8b3ce071342dfaea2a14357431d94b82M,]
1e86909765bd5603a152bbd55e511e0586f1b77fL,]
36222f8eb2ccf21ca345e15186cea64506581543K,]
9aa8f3d1df6ff6d266a531432fe9ea0bb56ad3c3J,]
00e3756119a91432622f6982b59ecd24a1340fbeI,]
1551d42b24a5b1e1ead5f0793e807869249ab93eH,]
7d7de228c501ef486534cca1829378eef8ef1081G,]
28142adcd8a406110c76dbb8e324dc211f3944d1F,]
9d2c1271f1219522d13f150c2b04123bef300dd9E,]
50158bc1a8a67295ab7bce0550886a9859000dc2D,]
49ed15db181c74c7067ec01800fb5392411c868cC,]
368427e6e351d1ac0ef97e824968ed15d0dc3d4dB,]
f52e7afce70597024c3be7df105185dd59a2c8e6A,]
fd443b2ce70c48202ba26cbc6caa471ae262e270@,]
003d5a65de0ac72daaf105ded903cb3eb88585b3?,]
11ff11e3aedaa41a67bea3623e5d2a805db6166e>,]
d65e79756ac6817d4780286045a35d34aaaaf836=,]
76c0579c23504531220601029d455dca6413b628<,]
4e63eed9e709b6c8e20a4a68300883898c7d8f37;,]
daf38d927e2b21c885efdb4b2cc46a2d9f47d679:,]
76eea8436996c7e9c8f7ad3dac34a12865edab249,]
892b955b6fb175c92f3f294ab431f97a8827748d8,]
17007f5e69efcfeff03853a33121943e2b4df4227,]
24cece61e2128780072bc58f90b8ba47f624bc276,]
f06554b06ac49f129086c8889690faaa761398bb5,]
59b3e2060ef7108c9170975219aae410f52ba0b84,]
208aee805004d575035284b1c232209e9fa26b0e3,]
3b2c76827fb4ad1b2da0d0870441e77a27ee37de2,]
177f9ad15ae9420c5c22f20da9a7c8e8dad4f32d1,]
451da9c5558de4c75f01582292063a7c980292080,]
e51582689653f238029d984cd1780c93ef672771/,]
50c42217e3c5b52eb1732f4193bf452dcc0de71b.,]
0db38d32069f3341d34c35085dc009a85ba13c13-,]
8de2fdb04edce612738eb51e14ecc426381f8ed8,,]
0f278cf94ac0d7fe15a7c4e0f283446e9fc07474+,]
eecf3aaa6aadf48778bb1daa6b09d011632b9f55*,]
b8645fcfdf5af5759dc20ae769b96be510bdff1a),]
39ac2e0fc4ec63753306f99e71e0f38133e58ead(,]
87fbf4fa017a90b5ff819bcfca17fb52d6f6a790',]
f1948a2d5dc8745f725e3ba0b24e14847778cb19&,]
4cb33680dda1fa1f0bad1ca52e07a8a34a500104%,]
8b1d8d46836a6d5eb4355315b64d85c128cbff27$,]
29f3f5918946bf0a4d75bf5244f993847d03e26c#,]
07d847f310d5fa9138f461f0a25c5e0024f1c4af",]
e95ecb39639ce118c7ddd5bd7892378eacdd105f!,]
cb4710f77feed90ae01b332c492853a5b20e2c7d ,]
a2e89c6111f3e306c56472306795af290ffb29af,]
57d70e73a995be26f01ae51f321fdaf42a089bf8,]
e2e60f19214efaa7d842b4a3b3b322964bf78dc7,]
973f17392cb7b417271e9d482d17a44a8c70c70a,]
f5222809526d8a419a1752547880ba0a9013a8ca,]
4fc240d0d9e690cb9b0bcb2f8a5e5ca918b01410,]
1cdc911f5a1b7a770b2e27bf4ebfae04c003a616,]
11825521850926501e3f353ffb7cf14b0c389320,]
4b1ed99c65d500d4a610813736169851cb496810,]
fe0ae75e97abe2686e6bc8cbe94bfd08934e36da,]
a9d9352d43986d4a5a3554a84b99580225ec00cf,]
c5cf25551312490d3f3f3a6b62c5c3492b63f1f1,]
0ec3651f70a50c371a1f9502fc7d3eab272d5cff,]
0f007df1707d77a72237248b0d7fd93b37fc9db7,]
6125b966172dd6cde3563f2ae10d8f782d14e1de,]
78c295cfd7469cd3d494a48df7bd7748139e0660,]
30fae8663ffba4f4abca068a9bc8735a590a9bc5,]
ce8411564f95396b503868217469e2aaf1b996c9,]
83cf2b3372ef98f7fa5caf94aa44e7262ee47519
,]
7edaa9cc255ba8e0938cb563110b204a4f393d60,]
1c1ff93040a96dfe9f1309bfe34a989d5f93bb4f,]
fb2db075fa0230289a4f05caf2127b95fcc9aa9c
,]
4712e0a50083a6bda848bf4a65fe214f0f6a7069	,]
6e39523a0acd9855ff465598253c323f7dfd3cda,]
6718cc5cd4e1484990ee79a8c3cffaad6d7271c3,]
d62de5f995164fff50f5ce61c0113f6bc9f04225,]
e76af50e96b12fc507e73b025fe9da4a99600af9,]
3a05eea36ffdbcf0625d5154a6458e75ca835971,]
02cc6a5944d57d2353a55639c7b77336,]
c5cf25551312490d3f3f3a6b62c5c3492b63f1f1,]
5b0ccfcd8135c9599f8088443ed7de1874fa1c97k<0F><00><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><0F><00>S<00><17>'GGhttp://www.cs.duke.edu/courses/cps296.4/spring04/papers/Adleman94.pdfMolecular Computation of Solutions to Combinatorial Problemsbiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949y	M'GGhttp://en.wikipedia.org/wiki/Pcrwikipediabiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949<EFBFBD>E
a<>+GGhttps://github.com/ibab/tensorflow-wavenet[Python] Implementation with the TensorFlow Machine Intelligence libraryaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>6
W<>	+GGhttps://github.com/basveeling/wavenet[Python] Implementation with the Keras Neural Networks libraryaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>5
<00>W+GGhttps://deepmind.com/blog/wavenet-generative-model-raw-audio/Announcement and interactive examplesaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>	U_+GGhttps://arxiv.org/pdf/1609.03499.pdfWaveNet: A Generative Model for Raw Audioaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>:
	e[UGGhttp://ftp.cs.ucla.edu/pub/stat_ser/r360.pdfThe algorithmization of counterfactualsartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>=	mYUGGhttp://ftp.cs.ucla.edu/pub/stat_ser/R218-B-L.pdfCausal diagrams for empirical researchartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>9	uIUGGhttp://ftp.cs.ucla.edu/pub/stat_ser/r156-reprint.pdfA theory of inferred causationartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>[

c<>UGGhttp://ftp.cs.ucla.edu/pub/stat_ser/r30.pdfReverend Bayes on inference engines: A distributed hierarchical approachartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>i	<00>!<21>=GGhttp://airesearch.com/wp-content/uploads/2016/01/deepmind-mastering-go.pdfMastering the Game of Go with Deep Neural Networks and Tree Searchartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>	W#=GGhttp://bayes.cs.ucla.edu/jp_home.htmlJudea Pearlartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>5	yU=GGhttp://www.csee.umbc.edu/courses/471/papers/turing.pdfComputing Machinery and Intelligenceartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>S<00><0B>{=GGhttps://github.com/papers-we-love/papers-we-love/blob/master/artificial_intelligence/3-bayesian-network-inference-algorithm.pdfAnalysis of Three Bayesian Network Inference Algorithms: Variable Elimination, Likelihood Weighting, and Gibbs Samplingartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD><00>'<27>Q#GGhttps://www.ics.uci.edu/~fielding/pubs/dissertation/fielding_dissertation.pdfArchitectural Styles and the Design of Network-based Software Architectures (REST) by Roy Fieldingapi_design/2017-09-11T23:06:15.1943510742017-09-11T23:06:15.194351074<EFBFBD>f
g<>gGGhttp://www.bodden.de/pubs/far+14flowdroid.pdfFlowDroid: Precise Context, Flow, Field, Object-sensitive and Lifecycle-aware Taint Analysis for Android Appsandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>{
u<>GGhttp://www.cse.psu.edu/~duo114/pubs/octeau-sec13.pdfEffective Inter-Component Communication Mapping in Android with Epicc: An Essential Step Towards Holistic Security Analysisandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>?
<00>uGGhttps://www.eecs.berkeley.edu/~daw/papers/intents-mobisys11.pdfAnalyzing Inter-Application Communication in Androidandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>M

<00>+qGGhttp://blog.sei.cmu.edu/post.cfm/secure-coding-tools-analyzing-android-apps-118Two Secure Coding To/<2F>"-<2D>s&<26>.<2E><00><>|,<2C>e*<2A>Ue<>C)<29>4'<27>"%<25>#t"c!O:&Y0<0F><0F>5<0E>Y<0C>

><0C>	o<06><07><06>[N<03>u<04>
<01>
<01><00><08><0E><03>j4<05><04>.
<0A>
Z<00>%<02><02>Z<00>	
vh3	<0B>.#
>
<EFBFBD>W	1g<0E>6q
http://sigops.org/sosp/sosp13/papers/p33-david.pdf95o
http://www.sci.utah.edu/~bsumma/projects/weaving/8_<04>A
http://www.disneyresearch.com/project/high-quality-single-shot-capture-of-facial-geometry/7d<04>K
http://www.disneyresearch.com/project/coupled-3d-reconstruction-of-sparse-facial-hair-and-skin/6=
http://shapegrammar.org/53k
http://shapegrammar.org/ifip/SGBestPapers72.pdf4=
http://cs.brown.edu/courses/csci2370/2000/1999/cabral.pdf3F<04>
http://peterwonka.net/Publications/pdfs/2014.SG.Lipp.PushPull.pdf2[<04>9
http://www.peterwonka.net/Publications/pdfs/2003.SG.Wonka.InstantArchitecture.high.pdf1h<04>S
http://www.peterwonka.net/Publications/pdfs/2006.SG.Mueller.ProceduralModelingOfBuildings.final.pdf0Q<04>%
http://www.proun-game.com/Oogst3D/CODING/InteriorMapping/InteriorMapping.pdf/?<04>

http://research.microsoft.com/en-us/um/people/cohen/bs.pdf.A<04>
http://www.crytek.com/download/Light_Propagation_Volumes.pdf-9w
https://github.com/luanfujun/deep-photo-styletransfer,(U
https://arxiv.org/pdf/1703.07511.pdf+X<04>3
http://www.cs.tau.ac.il/~dcor/articles/2013/3-Sweep-Extracting-Editable-Objects.pdf*I<04>
http://research.microsoft.com/pubs/155416/kinectfusion-uist-comp.pdf)@<04>
http://www.cs.jhu.edu/~misha/Code/PoissonRecon/Version5.71/(I<04>
http://research.microsoft.com/en-us/um/people/hoppe/poissonrecon.pdf'S<04>)
http://www.cs.rpi.edu/~cutler/classes/advancedgraphics/S08/lectures/kajiya.pdf&G<04>
http://www.cs.northwestern.edu/~ago820/cs395/Papers/Phong_1975.pdf%c<04>I
http://page.mi.fu-berlin.de/block/htw-lehre/wise2015_2016/bel_und_rend/skripte/gouraud1971.pdf$A
http://gigavoxels.imag.fr/#6q
http://maverick.inria.fr/Publications/2009/CNLE09/"A<04>
http://maverick.inria.fr/Publications/2009/CNLE09/CNLE09.pdf!K<04>
https://www.cs.drexel.edu/~david/Classes/CS586/Papers/p343-whitted.pdf H<04>
http://graphics.stanford.edu/papers/stabilization/karpenko_gyro.pdf.a
http://barroso.org/publications/isca00.pdfz<04>w
https://www.researchgate.net/publication/220080099_MEXICA_A_computer_model_of_a_cognitive_account_of_creative_writingi<04>U
http://www.ams.org/journals/tran/1965-117-00/S0002-9947-1965-0170805-7/S0002-9947-1965-0170805-7.pdf0e
http://www.turingarchive.org/browse.php/B/12=
https://www.cs.virginia.edu/~robins/Turing_Paper_1936.pdf\<04>;
http://gatekeeper.dec.com/ftp/pub/dec/SRC/publications/broder/positano-final-wpnums.pdfF<04>
http://adam.chlipala.net/papers/SqlcachePOPL17/SqlcachePOPL17.pdf*Y
http://www.vldb.org/conf/1994/P439.PDF<17><04>%
https://github.com/papers-we-love/papers-we-love/blob/master/caching/a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdfS<04>)
https://homes.cs.washington.edu/~luisceze/publications/dnastorage-asplos16.pdfD<04>
http://www.dna.caltech.edu/courses/cs191/paperscs191/turing.pdfJ<04>
http://www.cs.duke.edu/courses/cps296.4/spring04/papers/Adleman94.pdf$M
http://en.wikipedia.org/wiki/Pcr.a
https://github.com/ibab/tensorflow-wavenet)W
https://github.com/basveeling/wavenetB<04>
https://deepmind.com/blog/wavenet-generative-model-raw-audio/(U
https://arxiv.org/pdf/1609.03499.pdf0e
http://ftp.cs.ucla.edu/pub/stat_ser/r360.pdf
4m
http://ftp.cs.ucla.edu/pub/stat_ser/R218-B-L.pdf8u
http://ftp.cs.ucla.edu/pub/stat_ser/r156-reprint.pdf/c
http://ftp.cs.ucla.edu/pub/stat_ser/r30.pdf
O<04>!
http://airesearch.com/wp-content/uploads/2016/01/deepmind-mastering-go.pdf	)W
http://bayes.cs.ucla.edu/jp_home.html:y
http://www.csee.umbc.edu/courses/471/papers/turing.pdf<07><04>
https://github.com/papers-(<04>https://githu+<2B><04>
https://github.com/papers-we-love/papers-we-love/blob/master/sublinear_algorithms/1985-Flajolet-Probabilistic-counting.pdf
(Q<04>%
http://www.proun-game.com/Oogst3D/CODING/InteriorMapping/InteriorMapping.pdf/$X<04>3
http://www.cs.tau.ac.il/~dcor/articles/2013/3-Sweep-Extracting-Editable-Objects.pdf* F<04>
http://research.microsoft.com/pubs/80693/vl2-sigcomm09-final.pdf<00>A
http://gigavoxels.imag.fr/#
<00>o<0E>
<0C><0B>
<EFBFBD>	<09><08><07><06><04><03><02><00>
<01><00>]<5D>#3<>GG
30fae8663ffba4f4abca068a9bc8735a590a9bc5A framework for automated generation of questions across formal domains.pdfcomputer_education/a framework for automated generation of questions across formal domains2017-09-11T23:06:05.6346818852017-09-11T23:06:05.634681885<EFBFBD>
]<5D>+1<>#GG78c295cfd7469cd3d494a48df7bd7748139e0660digital_video_stabilization_and_rolling_shutter_correction_using_gyroscopes.pdfcomputer_graphics/digital video stabilization and rolling shutter correction using gyroscopes2017-09-11T23:06:05.6673129882017-09-11T23:06:05.667312988<EFBFBD>
]<5D>?<3F>GGce8411564f95396b503868217469e2aaf1b996c9mexica-a-computer-model-of-a-cognitive-account-of-creativing-writing.pdfcomputational_creativity/mexica a computer model of a cognitive account of creativing writing2017-09-11T23:06:05.5951909182017-09-11T23:06:05.595190918<EFBFBD>
]<5D>Q{GG
83cf2b3372ef98f7fa5caf94aa44e7262ee47519story-of-squeak-a-practical-smalltalk-written-in-itself.pdfcomp_sci_fundamentals_and_history/story of squeak a practical smalltalk written in itself2017-09-11T23:06:05.4806750492017-09-11T23:06:05.480675049<EFBFBD>7]<5D>9Q<39>1EE
7edaa9cc255ba8e0938cb563110b204a4f393d60recursive-functions-of-symbolic-expressions-and-their-computation-by-machine-parti.pdfcomp_sci_fundamentals_and_history/recursive functions of symbolic expressions and their computation by machine parti2017-09-11T23:06:05.475392092017-09-11T23:06:05.47539209<EFBFBD>S	]UQMGG
1c1ff93040a96dfe9f1309bfe34a989d5f93bb4fhints-for-computer-system-design.pdfcomp_sci_fundamentals_and_history/hints for computer system design2017-09-11T23:06:05.4713090822017-09-11T23:06:05.471309082<EFBFBD>	
]<5D>	Q<>
GG
fb2db075fa0230289a4f05caf2127b95fcc9aa9cearly-lisp-history-1956-1959-herbert-stoyan-html-rendering.pdfcomp_sci_fundamentals_and_history/early lisp history 1956 1959 herbert stoyan html rendering2017-09-11T23:06:05.3734951172017-09-11T23:06:05.373495117<EFBFBD>[		]]QUGG
4712e0a50083a6bda848bf4a65fe214f0f6a7069axiomatic-basis-computer-programming.pdfcomp_sci_fundamentals_and_history/axiomatic basis computer programming2017-09-11T23:06:05.3045129392017-09-11T23:06:05.304512939<EFBFBD>r
]<5D>
<1D>GG6e39523a0acd9855ff465598253c323f7dfd3cdaa-program-optimization-for-automatic-database-result-caching.pdfcaching/a program optimization for automatic database result caching2017-09-11T23:06:05.2589628912017-09-11T23:06:05.258962891<EFBFBD>
]<5D><1D>GG
6718cc5cd4e1484990ee79a8c3cffaad6d7271c3a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdfcaching/a constant algorithm for implementing the lfu cache eviction scheme2017-09-11T23:06:05.2532370612017-09-11T23:06:05.253237061<EFBFBD>
]<5D>)<1D>!GGd62de5f995164fff50f5ce61c0113f6bc9f042252q-a-low-overhead-high-performance-buffer-management-replacement-algorithm.pdfcaching/2q a low overhead high performance buffer management replacement algorithm2017-09-11T23:06:05.2014589842017-09-11T23:06:05.201458984<EFBFBD>:	]O+GGG
e76af50e96b12fc507e73b025fe9da4a99600af9shazam-audio-search-algorithm.pdfaudio_comp_sci/shazam audio search algorithm2017-09-11T23:06:05.1690869142017-09-11T23:06:05.169086914<EFBFBD>j	]+wGG
3a05eea36ffdbcf0625d5154a6458e75ca835971an-ethnographic-and-technological-study-of-breakbeats.pdfaudio_comp_sci/an ethnographic and technological study of breakbeats2017-09-11T23:06:04.4569431152017-09-11T23:06:04.456943115<EFBFBD>]<5D>=<3D>GG
02cc6a5944d57d2353a55639c7b77336b94f29b6efficient-selectivity-and-backup-operators-in-monte-carlo-tree-search.pdfartificial_intelligence/efficient selectivity and backup operators in monte carlo tree search2017-09-11T23:06:04.4221010742017-09-11T23:06:04.422101074<EFBFBD>U	]a=YGG
ac14e6bf50d1491043baf1d854727a68f5f3f51d3-bayesian-network-inference-algorithm.pdfartificial_intelligence/3 bayesian network inference algorithm2017-09-11T23:06:04.4156010742017-09-11T23:06:04.415601074<EFBFBD>
	])#!EE
bd9e0c2f5aaf68d784862ab361cc1a41fc9b32cdapi-design.pdfapi_design/api design2017-09-11T23:06:04.390895022017-09-11T23:06:04.39089502

<01>x
<0A>
p{
b	<09>	w<07>#1]<04><03><02>
<01><00><00>#]<5D>5#<23>-GG
,29f3f5918946bf0a4d75bf5244f993847d03e26cnetwork-challenges-of-data-recovery-in-erasure-coded-distributed-storage-systems.pdfdatastores/network challenges of data recovery in erasure coded distributed storage systems2017-09-11T23:06:07.3144809572017-09-11T23:06:07.314480957<EFBFBD>"]<5D>1#<23>)GG
)07d847f310d5fa9138f461f0a25c5e0024f1c4afmegastore-providing-scalable-highly-available-storage-for-interactive-services.pdfdatastores/megastore providing scalable highly available storage for interactive services2017-09-11T23:06:07.2573869632017-09-11T23:06:07.257386963<EFBFBD>~!]<5D>#<23>
GG
'e95ecb39639ce118c7ddd5bd7892378eacdd105ffreenet-a-distributed-anonymous-information-and-retrieval-system.pdfdatastores/freenet a distributed anonymous information and retrieval system2017-09-11T23:06:07.2520090332017-09-11T23:06:07.252009033<EFBFBD>* 	]C#;GG
&cb4710f77feed90ae01b332c492853a5b20e2c7dflat-datacenter-storage.pdfdatastores/flat datacenter storage2017-09-11T23:06:07.2170839842017-09-11T23:06:07.217083984<EFBFBD>Z	]s#kGG
%a2e89c6111f3e306c56472306795af290ffb29afdynamo-amazons-highly-available-key-value-store.pdfdatastores/dynamo amazons highly available key value store2017-09-11T23:06:07.1755410162017-09-11T23:06:07.175541016<EFBFBD>Q	]k#aGG
"57d70e73a995be26f01ae51f321fdaf42a089bf8database-metatheory--asking-the-big-queries.pdfdatastores/database metatheory asking the big queries2017-09-11T23:06:07.1400959472017-09-11T23:06:07.140095947<EFBFBD>o
]<5D>#GG
$e2e60f19214efaa7d842b4a3b3b322964bf78dc7bigtable-a-distributed-storage-system-for-structured-data.pdfdatastores/bigtable a distributed storage system for structured data2017-09-11T23:06:07.0712219242017-09-11T23:06:07.071221924<EFBFBD>3	]G-?GG
#973f17392cb7b417271e9d482d17a44a8c70c70alevel-ancestor-simplified.pdfdata_structures/level ancestor simplified2017-09-11T23:06:07.0427290042017-09-11T23:06:07.042729004<EFBFBD>	]/-'GG
 f5222809526d8a419a1752547880ba0a9013a8calca-revisited.pdfdata_structures/lca revisited2017-09-11T23:06:07.0380878912017-09-11T23:06:07.038087891<EFBFBD>!	]5--GG
4fc240d0d9e690cb9b0bcb2f8a5e5ca918b01410ideal-hash-trees.pdfdata_structures/ideal hash trees2017-09-11T23:06:07.0322880862017-09-11T23:06:07.032288086<EFBFBD>1	]E-=GG<00>1cdc911f5a1b7a770b2e27bf4ebfae04c003a616epidemic-broadcast-trees.pdfdata_structures/epidemic broadcast trees2017-09-11T23:06:06.9530539552017-09-11T23:06:06.953053955<EFBFBD>	]''GG
11825521850926501e3f353ffb7cf14b0c389320tidy_data.pdfdata_science/tidy data2017-09-11T23:06:06.8811560062017-09-11T23:06:06.881156006<EFBFBD>]<5D>'/<2F>GG
4b1ed99c65d500d4a610813736169851cb496810a-comprehensive-study-of-convergent-and-communative-replicated-data-types.pdfdata_replication/a comprehensive study of convergent and communative replicated data types2017-09-11T23:06:06.6977900392017-09-11T23:06:06.697790039<EFBFBD>r
]<5D>	%<25>
GGPfe0ae75e97abe2686e6bc8cbe94bfd08934e36daa-new-approach-to-linear-filtering-and-prediction-problems.pdfdata_fusion/a new approach to linear filtering and prediction problems2017-09-11T23:06:06.6447390142017-09-11T23:06:06.644739014<EFBFBD>"	]5/-GG
!a9d9352d43986d4a5a3554a84b99580225ec00cfdata-compression.pdfdata_compression/data compression2017-09-11T23:06:06.5855659182017-09-11T23:06:06.585565918<EFBFBD>	
])'!GGFc5cf25551312490d3f3f3a6b62c5c3492b63f1f1ntru-prime.pdfcryptography/ntru prime2017-09-11T23:06:06.5104699712017-09-11T23:06:06.510469971<EFBFBD>L	]c'[GG
0ec3651f70a50c371a1f9502fc7d3eab272d5cffcommunication-theory-of-secrecy-systems.pdfcryptography/communication theory of secrecy systems2017-09-11T23:06:06.4779880372017-09-11T23:06:06.477988037<EFBFBD>	
])1!GG-0f007df1707d77a72237248b0d7fd93b37fc9db7pushpull++.pdfcomputer_graphics/pushpull++2017-09-11T23:06:06.0258610842017-09-11T23:06:06.025861084<EFBFBD>l	
]1wGG16125b966172dd6cde3563f2ae10d8f782d14e1deimaging_vector_fields_using_line_integral_convolution.pdfcomputer_graphics/imaging vector fields using line integral convolution2017-09-11T23:06:05.8729819342017-09-11T23:06:05.872981934

$-g<0E>

S<0B>
<EFBFBD>	<09>	3<08>t<06>-<02><04>
$
$<00>t0
]<5D>5}EE
8451da9c5558de4c75f01582292063a7c98029208a-hundred-impossibility-proofs-for-distributed-computing.pdfdistributed_systems/a hundred impossibility proofs for distributed computing2017-09-11T23:06:07.682752932017-09-11T23:06:07.68275293<05>
~]<5D>?5<>7GGf06554b06ac49f129086c8889690faaa761398bbbeehive-lookup-performance-for-power-law-query-distributions-in-peer-to-peer-overlays.pdfdistributed_systems/beehive lookup performance for power law query distributions in peer to peer overlays2017-09-11T23:06:07.8799250492017-09-11T23:06:07.8799250492]<5D>75<37>/GG59b3e2060ef7108c9170975219aae410f52ba0b8a-versatile-scheme-for<6F>B1	
]S5KGGr177f9ad15ae9420c5c22f20da9a7c8e8dad4f32da-note-on-distributed-computing.pdfdistributed_systems/a note on distributed computing2017-09-11T23:06:07.8596940922017-09-11T23:06:07.859694092<EFBFBD>#]<5D>5#<23>-GG
,29f3f5918946bf0a4d75bf5244f993847d03e26cnetwork-challenges-of-data-recovery-in-erasure-coded-distributed-storage-systems.pdfdatastores/network challenges of data recovery in erasure coded distributed storage systems2017-09-11T23:06:07.3144809572017-09-11T23:06:07.314480957<EFBFBD>52]<5D>C5<43>;GG
63b2c76827fb4ad1b2da0d0870441e77a27ee37dea-response-to-cheriton-and-skeens-criticism-of-causal-and-totally-ordered-communication.pdfdistributed_systems/a response to cheriton and skeens criticism of causal and totally ordered communication2017-09-11T23:06:07.8636289062017-09-11T23:06:07.863628906<00>]S5KGG177f9ad15ae9420c5c22f20da9a7c8e8dad4f32da-note-on-distributed-computing.pdfdistributed_systems/a note on distributed computing2017-09-11T23:06:07.8596940922017-09-11T23:06:07.859694092<EFBFBD>m/	]}5uGG
5e51582689653f238029d984cd1780c93ef672771a-history-of-the-virtual-synchrony-replication-model.pdfdistributed_systems/a history of the virtual synchrony replication model2017-09-11T23:06:07.6757680662017-09-11T23:06:07.675768066<EFBFBD>.	]'/GG
150c42217e3c5b52eb1732f4193bf452dcc0de71bprimecoin.pdfdigital_currency/primecoin2017-09-11T23:06:07.6694719242017-09-11T23:06:07.669471924<EFBFBD>-	]%/GG
30db38d32069f3341d34c35085dc009a85ba13c13peercoin.pdfdigital_currency/peercoin2017-09-11T23:06:07.6654379882017-09-11T23:06:07.665437988<EFBFBD>,	]#/GG
48de2fdb04edce612738eb51e14ecc426381f8ed8bitcoin.pdfdigital_currency/bitcoin2017-09-11T23:06:07.6606379392017-09-11T23:06:07.660637939<EFBFBD>+	]91GG
20f278cf94ac0d7fe15a7c4e0f283446e9fc07474out-of-the-tar-pit.pdfdesign/out of the tar pit2017-09-11T23:06:07.6535400392017-09-11T23:06:07.653540039<EFBFBD>\*	]u#mGG
0eecf3aaa6aadf48778bb1daa6b09d011632b9f55warp-multi-key-transactions-for-key-value-stores.pdfdatastores/warp multi key transactions for key value stores2017-09-11T23:06:07.6474089362017-09-11T23:06:07.647408936<EFBFBD>\)	]u#mGG
/b8645fcfdf5af5759dc20ae769b96be510bdff1atransactional-storage-for-geo-replicated-systems.pdfdatastores/transactional storage for geo replicated systems2017-09-11T23:06:07.6410458982017-09-11T23:06:07.641045898<EFBFBD>@(	]Y#QGG
-39ac2e0fc4ec63753306f99e71e0f38133e58eadtao-facebook-distributed-datastore.pdfdatastores/tao facebook distributed datastore2017-09-11T23:06:07.5965590822017-09-11T23:06:07.596559082<EFBFBD>F'	]_#WGG
*87fbf4fa017a90b5ff819bcfca17fb52d6f6a790stasis-flexible-transactional-storage.pdfdatastores/stasis flexible transactional storage2017-09-11T23:06:07.5536740722017-09-11T23:06:07.553674072<EFBFBD>k&
]<5D>#{GG
(f1948a2d5dc8745f725e3ba0b24e14847778cb19spartan-a-distributed-array-framework-with-smart-tiling.pdfdatastores/spartan a distributed array framework with smart tiling2017-09-11T23:06:07.4223029792017-09-11T23:06:07.422302979<EFBFBD>X%	]q#iGG
.4cb33680dda1fa1f0bad1ca52e07a8a34a500104spanner-google's-globally-distributed-database.pdfdatastores/spanner google's globally distributed database2017-09-11T23:06:07.3493959962017-09-11T23:06:07.349395996<EFBFBD>$]<5D>/#<23>'GG
+8b1d8d46836a6d5eb4355315b64d85c128cbff27rados-a-scalable-reliable-storage-service-for-petabyte-scale-storage-clusters.pdfdatastores/rados a scalable reliable storage service for petabyte scale storage clusters2017-09-11T23:06:07.3200139162017-09-11T23:06:07.320013916
<07>
<01><06><05>o<03>BR
F<02><0B>
<EFBFBD><08>
<01>?
Fa<00>bF	]u5kGG28142adcd8a406110c76dbb8e324dc211f3944d1high-level-specifications--lessons-from-industry.pdfdistributed_systems/high level specifications lessons from industry2017-09-11T23:06:08.4614240722017-09-11T23:06:08.461424072<EFBFBD>vE
]<5D>5GG9d2c1271f1219522d13f150c2b04123bef300dd9herbivore-a-scalable-and-efficient-protocol-for-anonymous.pdfdistributed_syst<73>
>]<5D>5<>GG
@11ff11e3aedaa41a67bea3623e5d2a805db6166ecopysets-reducing-the-frequency-of-data-loss-in-cloud-storage.pdfdistributed_systems/copysets reducing the frequency of data loss in cloud storage2017-09-11T23:06:08.1418569342017-09-11T23:06:08.141856934<EFBFBD>t:
]<5D>5{GG
>daf38d927e2b21c885efdb4b2cc46a2d9f47d679commodifying-replicated-state-machines-with-openreplica.pdfdistributed_systems/commodifying replicated state machines with openreplica2017-09-11T23:06:07.9118620612017-09-11T23:06:07.911862061<EFBFBD>)6	]951GG
;24cece61e2128780072bc58f90b8ba47f624bc27brewers-conjecture.pdfdistributed_systems/brewers conjecture2017-09-11T23:06:07.8881889652017-09-11T23:06:07.888188965<EFBFBD>15]<5D>?5<>7GG
:f06554b06ac49f129086c8889690faaa761398bbbeehive-lookup-performance-for-power-law-query-distributions-in-peer-to-peer-overlays.pdfdistributed_systems/beehive lookup performance for power law query distributions in peer to peer overlays2017-09-11T23:06:07.8799250492017-09-11T23:06:07.879925049<EFBFBD>)4]<5D>75<37>/GG
959b3e2060ef7108c9170975219aae410f52ba0b8a-versatile-scheme-for-routing-highly-variable-traffic-in-service-overlays-and-ip.pdfdistributed_systems/a versatile scheme for routing highly variable traffic in service overlays and ip2017-09-11T23:06:07.8742758792017-09-11T23:06:07.874275879<EFBFBD>3]<5D>5<>GG
7208aee805004d575035284b1c232209e9fa26b0ea-universal-modular-actor-formalism-for-artificial-intelligence.pdfdistributed_systems/a universal modular actor formalism for artificial intelligence2017-09-11T23:06:07.8694250492017-09-11T23:06:07.869425049	<09>
]<5D>5<>GG11ff11e3aedaa41a67bea3623e5d2a805db6166ecopysets-reducing-the-frequency-of-data-loss-in-cloud-storage.pdfdistributed_systems/copysets reducing the frequency of data loss in cloud storage2017-09-11T23:06:08.1418569342017-09-11T23:06:08.1418569<EFBFBD>K=	][5SGG
Dd65e79756ac6817d4780286045a35d34aaaaf836consistent-hashing-and-random-trees.pdfdistributed_systems/consistent hashing and random trees2017-09-11T23:06:08.1365800782017-09-11T23:06:08.136580078<0C><00>]<5D>;5<>3GG76c0579c23504531220601029d455dca6413b628consistent-global-states-of-distributed-systems-fundamental-concepts-and-mechanisms.pdfdistributed_systems/consistent global states of distributed systems fundamental concepts and mechani<6E>-<]<5D>;5<>3GG
E76c0579c23504531220601029d455dca6413b628consistent-global-states-of-distributed-systems-fundamental-concepts-and-mechanisms.pdfdistributed_systems/consistent global states of distributed systems fundamental concepts and mechanisms2017-09-11T23:06:08.1307338872017-09-11T23:06:08.130733887<EFBFBD>Y;	]i5aGG
?4e63eed9e709b6c8e20a4a68300883898c7d8f37consensus-in-presence-of-partial-synchrony.pdfdistributed_systems/consensus in presence of partial synchrony2017-09-11T23:06:07.9177128912017-09-11T23:06:07.917712891<00>]<5D>5<>GG76eea8436996c7e9c8f7ad3dac34a12865edab24chain-replication-for-supporting-high-throughput-and-availability.pdfdistributed_systems/chain replication for<6F>	9]<5D>5<>GG
B76eea8436996c7e9c8f7ad3dac34a12865edab24chain-replication-for-supporting-high-throughput-and-availability.pdfdistributed_systems/chain replication for supporting high throughput and availability2017-09-11T23:06:07.9060500492017-09-11T23:06:07.906050049<EFBFBD>m8	]}5uGG
=892b955b6fb175c92f3f294ab431f97a8827748dbyzantine-fault-tolerant-distributed-commit-protocol.pdfdistributed_systems/byzantine fault tolerant distributed commit protocol2017-09-11T23:06:07.9004890142017-09-11T23:06:07.900489014<EFBFBD>;7	]K5CGG
<17007f5e69efcfeff03853a33121943e2b4df422byzantine-chain-replication.pdfdistributed_systems/byzantine chain replication2017-09-11T23:06:07.8936340332017-09-11T23:06:07.893634033

<01>	
<0A>

/:
\	azv^r
<01>}<03><02><00>iJ	]y5qGG
P9aa8f3d1df6ff6d266a531432fe9ea0bb56ad3c3in-search-of-an-understandable-consensus-algorithm.pdfdistributed_systems/in search of an understandable consensus algorithm2017-09-11T23:06:08.4855869142017-09-11T23:06:08.485586914<EFBFBD>GM]<5D>U5<55>MGG
Mbde7543a8b3ce071342dfaea2a14357431d94b82kelips-building-an-efficient-and-stable-p2p-dht-through-increased-memory-and-background-overhead.pdfdistributed_systems/kelips building an efficient and stable p2p dht through increased memory and background overhead2017-09-11T23:06:08.5111398932017-09-11T23:06:08.511139893<EFBFBD>L	]/5'GG
N1e86909765bd5603a152bbd55e511e0586f1b77fjoin-calculus.pdfdistributed_systems/join calculus2017-09-11T23:06:08.5028688962017-09-11T23:06:08.502868896<EFBFBD>rK
]<5D>5{EE<00>36222f8eb2ccf21ca345e15186cea64506581543ironFleet-proving-practical-distributed-systems-correct.pdfdistributed_systems/ironfleet proving practical distributed systems correct2017-09-11T23:06:08.494632082017-09-11T23:06:08.49463208<EFBFBD>iI	]y5qGG
L00e3756119a91432622f6982b59ecd24a1340fbeimpossibility-of-consensus-with-one-faulty-process.pdfdistributed_systems/impossibility of consensus with one faulty process2017-09-11T23:06:08.4766879882017-09-11T23:06:08.476687988<EFBFBD>H]<5D>#5<>GG
K1551d42b24a5b1e1ead5f0793e807869249ab93eimplementing-the-omega-failure-detector-in-crash-recovery-failure-model.pdfdistributed_systems/implementing the omega failure detector in crash recovery failure model2017-09-11T23:06:08.4707060552017-09-11T23:06:08.470706055<EFBFBD>
G]<5D>5<>	EE
J7d7de228c501ef486534cca1829378eef8ef1081how-the-hidden-hand-shapes-the-market-for-software-reliability.pdfdistributed_systems/how the hidden hand shapes the market for software reliability2017-09-11T23:06:08.466872072017-09-11T23:06:08.46687207<EFBFBD>dF	]u5kGG
I28142adcd8a406110c76dbb8e324dc211f3944d1high-level-specifications--lessons-from-industry.pdfdistributed_systems/high level specifications lessons from industry2017-09-11T23:06:08.4614240722017-09-11T23:06:08.461424072<EFBFBD>xE
]<5D>5GG
G9d2c1271f1219522d13f150c2b04123bef300dd9herbivore-a-scalable-and-efficient-protocol-for-anonymous.pdfdistributed_systems/herbivore a scalable and efficient protocol for anonymous2017-09-11T23:06:08.4552490232017-09-11T23:06:08.455249023<EFBFBD>[D	]k5cGG
H50158bc1a8a67295ab7bce0550886a9859000dc2harvest-yield-and-scalable-tolerant-systems.pdfdistributed_systems/harvest yield and scalable tolerant systems2017-09-11T23:06:08.4413249512017-09-11T23:06:08.441324951<EFBFBD>rC
]<5D>5{EE<00>49ed15db181c74c7067ec01800fb5392411c868cepidemic-algorithms-for-replicated-database-maintenance.pdfdistributed_systems/epidemic algorithms for replicated database maintenance2017-09-11T23:06:08.371104982017-09-11T23:06:08.37110498<EFBFBD>OB	]_5WGG<00>368427e6e351d1ac0ef97e824968ed15d0dc3d4dend-to-end-arguments-in-system-design.pdfdistributed_systems/end to end arguments in system design2017-09-11T23:06:08.3673620612017-09-11T23:06:08.367362061<EFBFBD>oA	]5wGG
Cf52e7afce70597024c3be7df105185dd59a2c8e6eluding-carnivores-file-sharing-with-strong-anonymity.pdfdistributed_systems/eluding carnivores file sharing with strong anonymity2017-09-11T23:06:08.3627729492017-09-11T23:06:08.362772949<EFBFBD>@]<5D>!5<>GG
Ffd443b2ce70c48202ba26cbc6caa471ae262e270distributed-snapshots-determining-global-states-of-distributed-systems.pdfdistributed_systems/distributed snapshots determining global states of distributed systems2017-09-11T23:06:08.2626330572017-09-11T23:06:08.262633057<EFBFBD>t?
]<5D>5{GG
A003d5a65de0ac72daaf105ded903cb3eb88585b3dapper-a-large-scale-distributed-tracing-infrastructure.pdfdistributed_systems/dapper a large scale distributed tracing infrastructure2017-09-11T23:06:08.1625371092017-09-11T23:06:08.162537109
b}<0E>
<0A><0C><0B>
<EFBFBD>
v<08><07><06>8}F?U<00>vX
]<5D>5}GG
Z4329143e227370d931a207184f3b995c0cb5c8d5self-stabilizing-systems-in-spite-of-distributed-control.pdfdistributed_systems/self stabilizing systems in spite of distributed control2017-09-11T23:06:08.7082280272017-09-11T23:06:08.708228027<EFBFBD>MS	]]5UGG
Yf16c6ce0c7eabd4f5896962335879b3932138e52on-proof-and-progress-in-mathematics.pdfdistributed_systems/on proof and progress in mathematics2017-09-11T23:06:08.6447729492017-09-11T23:06:08.644772949<EFBFBD>Y]<5D>'5<>GG
X95d36d171e5e2183c424f535fad2e8053f5cec64sift-design-and-analysis-of-a-fault-tolerant-computer-for-aircraft-contro.pdfdistributed_systems/sift design and analysis of a fault tolerant computer for aircraft contro2017-09-11T23:06:08.7147629392017-09-11T23:06:08.714762939	<09><00>]w5oGG5eb4500b8053ac8dd1a21bfca10c818e1e0a2405simple-testing-can-prevent-most-critical-failures.pdfdistributed_systems/simple testing can prevent most critical failures2017-09-11T23:06:08.8323769532017-09-11T23:06:08.832376953	<09><00>]<5D>5}<7D>g[	]w5oGG
a5eb4500b8053ac8dd1a21bfca10c818e1e0a2405simple-testing-can-prevent-most-critical-failures.pdfdistributed_systems/simple testing can prevent most critical failures2017-09-11T23:06:08.8323769532017-09-11T23:06:08.832376953<EFBFBD>vZ
]<5D>5}GG
[65d3575b1c380b1bcc14ec69ccf6989c04be9493signal-&-collect-graph-algorithms-for-the-(semantic)-web.pdfdistributed_systems/signal & collect graph algorithms for the (semantic) web2017-09-11T23:06:08.8134960942017-09-11T23:06:08.813496094<EFBFBD>'W	]75/GG
W763d0321ced31b774bd4ba2f9f369c087cbd278epaxos-made-simple.pdfdistributed_systems/paxos made simple2017-09-11T23:06:08.7029479982017-09-11T23:06:08.702947998<EFBFBD>?V	]O5GGG
U43c7b3780b5864f99d042392d83ab331f7fddf2apaxos-made-moderately-complex.pdfdistributed_systems/paxos made moderately complex2017-09-11T23:06:08.6627680662017-09-11T23:06:08.662768066<EFBFBD>CU]<5D>Q5<51>IGG
V4bf4acf54bfd2e65b1ed31fe272670a7e276c534pastry-scalable-decentralized-object-location-and-routing-for-large-scale-peer-to-peer-systems.pdfdistributed_systems/pastry scalable decentralized object location and routing for large scale peer to peer systems2017-09-11T23:06:08.6551569822017-09-11T23:06:08.655156982<EFBFBD>eT	]y5qEE1a0ba12427c68642a4871677b9de7a337356b9f6p5-a-protocal-for-scalable-anonymous-communication.pdfdistributed_systems/p5 a protocal for scalable anonymous communication2017-09-11T23:06:08.649752932017-09-11T23:06:08.64975293<00>]]5UGGf16c6ce0c7eabd4f5896962335879b3932138e52on-proof-and-progress-in-mathematics.pdfdistributed_systems/on proof and progress in mathematics2017-09-11T23:06:08.6447729492017-09-11T23:06:08.644772949<EFBFBD>)R]<5D>75<37>/GG
Ra2e4dc4b1cce765255e4d15084811da125c564c5oblivious-routing-of-highly-variable-traffic-in-service-overlays-and-ip-backbones.pdfdistributed_systems/oblivious routing of highly variable traffic in service overlays and ip backbones2017-09-11T23:06:08.6341188962017-09-11T23:06:08.634118896<EFBFBD>Q]<5D>5<>GG
T3e375c8d996b8c46c83b9d3f72732d7477e5fd86mesos-a-platform-for-fine-grained-resource-sharing-in-the-data-center.pdfdistributed_systems/mesos a platform for fine grained resource sharing in the data center2017-09-11T23:06:08.6232319342017-09-11T23:06:08.623231934<EFBFBD>rP
]<5D>
5yGG
Sf3050b5586ddfec5da0d719338a6afa8b166985bmapreduce-simplified-data-processing-on-large-clusters.pdfdistributed_systems/mapreduce simplified data processing on large clusters2017-09-11T23:06:08.6067629392017-09-11T23:06:08.606762939<EFBFBD>xO
]<5D>5GG
Oc20baa16cb57ff4979569871d15294fa720bbc23life-beyond-distributed-transactions-an-apostates-opinion.pdfdistributed_systems/life beyond distributed transactions an apostates opinion2017-09-11T23:06:08.5616230472017-09-11T23:06:08.561623047<EFBFBD>-N]<5D>;5<>3GG
Q57efc2b9ba2a725af1d66cc43c472d0314190051large-scale-incremental-processing-using-distributed-transactions-and-notifications.pdfdistributed_systems/large scale incremental processing using distributed transactions and notifications2017-09-11T23:06:08.5383491212017-09-11T23:06:08.538349121

<01>G<00><0F><0F>yL<0E><0E><0E>i<
<0A>
<0A>
<0A>
[
X
.

<04><0C><0C>zM <0B><0B><0B>l>
*<00>,
<EFBFBD>
<EFBFBD>
<EFBFBD>
\
.

	<09>	<09>	y	L	<08><08><08>k><07>Z<07><07>\/<06><06>{N <05><05>
<01><05>l><04><04><03><03>|N <02><02><00>
<01><02>j=
<01>-]703d0b290a4ece50c17854ed72ecc808ce3e6f43<00>-]23c425f022baa054c68683eaf81f5d482915ce13<00>-]239ff60210c28900f866c588f40e974d897a9f62<00>-]1396a6cd134a7f41eeb1e5d4ca8d4edf6edfc432<00>-]557b1ec3182ccb3a902cc9904a443accb438842f<00>x76e1cf37ae212298802799c2c3588030d20a769f<00>=.70882fa7790685902d4d8b56ba08a361f6e74eb1<00>,]
76eea8436996c7e9c8f7ad3dac34a12865edab249<02>76c0579c23504531220601029d455dca6413b628<-]765e049036ca947af05fb5b4f29b9daf4b363558<00>,]
763d0321ced31b774bd4ba2f9f369c087cbd278eW6e39523a0acd9855ff465598253c323f7dfd3cda-]6995ac2e570960403c02250b02e64cafed8378fd<00>-]6980e1e551cadbde62454bedf5e1324032fa1e40<00>-]6848895fe48b0ca3b0bc34c1bcdf66eb58e64308<00>,]
6718cc5cd4e1484990ee79a8c3cffaad6d7271c3,]
66401c00817c71713e86438385d91956246aeaabf,]
65d3575b1c380b1bcc14ec69ccf6989c04be9493Z,]
64832c7b1602f0922e4e818ad045d1bb5ae95-]272ef349f3b3561588a87a070de802c3c0246394<00>-]472f436ad317b23d7bd1ad53fcb4f23e8f0997a7<00>-]16c8ad89060897e39803a175470d7990bd40cd2b<00>-]59a968fa431e7117aa11005ed98ab39f1efddc30<00>,]
5ac2852c69cc7bda25677129da011dec23fc3d77v,]
59b3e2060ef7108c9170975219aae410f52ba0b84-]59776eb2358b4be265e7dae9df4f946dab25bf6f<00>,]
57efc2b9ba2a725af1d66cc43c472d0314190051N,]
57d70e73a995be26f01ae51f321fdaf42a089bf8,]
530b50510808903545d298de7e19d6e5463a72cdd,]
50c42217e3c5b52eb1732f4193bf452dcc0de71b.-]5046034fe0cddda681ad9374d306fd27eec8b5fb<00>,]
50158bc1a8a67295ab7bce0550886a9859000dc2D,]
4fc240d0d9e690cb9b0bcb2f8a5e5ca918b01410,]
4e63eed9e709b6c8e20a4a68300883898c7d8f37;,]
4cb33680dda1fa1f0bad1ca52e07a8a34a500104%,]
4bf4acf54bfd2e65b1ed31fe272670a7e276c534U,]
4ba0079fbfaf8a49f36f4e400f44c17b7f4552d4|-]4b85765a808e4c29f05bc48a17a2dced1702db9d<00>,]
4b1ed99c65d500d4a610813736169851cb496810,]
49ed15db181c74c7067ec01800fb5392411c868cC,]
4712e0a50083a6bda848bf4a65fe214f0f6a7069	,]
451da9c5558de4c75f01582292063a7c980292080,]
43c7b3780b5864f99d042392d83ab331f7fddf2aV,]
4329143e227370d931a207184f3b995c0cb5c8d5X,]
3e375c8d996b8c46c83b9d3f72732d7477e5fd86Q,]
3b2c76827fb4ad1b2da0d0870441e77a27ee37de2,]
3a05eea36ffdbcf0625d5154a6458e75ca835971,]
39ac2e0fc4ec63753306f99e71e0f38133e58ead(,]
381c0200a69d43c6605079aaf73beace048b76a6,]
368427e6e351d1ac0ef97e824968ed15d0dc3d4dB,]
36222f8eb2ccf21ca345e15186cea64506581543K-]3547ac839d02f6efe3f6f76a8289738a22528442<00>,]
30fae8663ffba4f4abca068a9bc8735a590a9bc5-]30ef9946a1733c097d541ffaae8e95f0af862a08<00>-]30baa244b66e81d737ccf9f667c9bfca4f0c18f1<00>,]
2db53cdcf4ba7c67321c022954c2b2be9c8a40bdi,]
29f3f5918946bf0a4d75bf5244f993847d03e26c#,]
28142adcd8a406110c76dbb8e324dc211f3944d1F,]
24cece61e2128780072bc58f90b8ba47f624bc276-]223b694fb70d4bd18ba0f4bd73ff3c6bc8f6370a<00>,]
2128052ca0319cdf9c9256eb52f26a23c6527094t,]
208aee805004d575035284b1c232209e9fa26b0e3,]
1e86909765bd5603a152bbd55e511e0586f1b77fL,]
1cdc911f5a1b7a770b2e27bf4ebfae04c003a616,]
1c1ff93040a96dfe9f1309bfe34a989d5f93bb4f,]
1a0ba12427c68642a4871677b9de7a337356b9f6T,]
18a74ae5e33b76a0528d0724d5c55a98dabe0b1fn,]
177f9ad15ae9420c5c22f20da9a7c8e8dad4f32d1,]
17007f5e69efcfeff03853a33121943e2b4df4227,]
158d08ec7c2134382e20b44001903ad5b8a521b2l,]
1551d42b24a5b1e1ead5f0793e807869249ab93eH,]
11ff11e3aedaa41a67bea3623e5d2a805db6166e>,]
11825521850926501e3f353ffb7cf14b0c389320,]
0f278cf94ac0d7fe15a7c4e0f283446e9fc07474+,]
0f007df1707d77a72237248b0d7fd93b37fc9db7,]
0ec3651f70a50c371a1f9502fc7d3eab272d5cff,]
0db38d32069f3341d34c35085dc009a85ba13c13--]09ac606ba306a1bea91642deb2af0909360b038f<00>,]
07f82eecbe3d530e3f967342245a4d5c8e41c05be,]
07d847f310d5fa9138f461f0a25c5e0024f1c4af"-]07ad71a8d82bf51e0b5d1d892aa6a10673a3b830<00>,]
0404bd58e5f1edbd288cd69fcbc224485af415bfs,]
02cc6a5944d57d2353a55639c7b77336b94f29b6,]
016f4930ad10f8097c42e5294b56d25bfb3c121fq,]
00e3756119a91432622f6982b59ecd24a1340fbeI,]
003d5a65de0ac72daaf105ded903cb3eb88585b3?
<00>E<00>f9<07><07><07>W*<06><06><06>rE<05><05><05>a3<04><0F><0F>yKO<0E><0E>!<0E>i<
<0A>
<0A>
<0A>
Z
,<0C><0C><0C>xJ<00><0B><0B><0B>i<}
<EFBFBD><03>
<EFBFBD>
<EFBFBD>
Y<04>
+	<09>	<09>	<09>	x	J	<08><08><08><03><03><03>pC<02><02><02>b5
<01>
<01>
<01>
S
%-]9b8aec8ef5c67da463f5ec7c174570eb7d1643a8<00><02>d0d8b7501d7f75613d5493d706d6d81852a73d6e<00>-]fec6b29569eac1a340990bb07e90355efd2434ec<00>,]
fe0ae75e97abe2686e6bc8cbe94bfd08934e36da,]
fd443b2ce70c48202ba26cbc6caa471ae262e270@,]
fc11031895c302dc52404d34de58af1a72f3b817g,]
fb2db075fa0230289a4f05caf2127b95fcc9aa9c
-]f6dce666a0f64f97f380f99cba7f14e24d5f54ad<00>,]
f52e7afce70597024c3be7df105185dd59a2c8e6A,]
f5222809526d8a419a1752547880ba0a9013a8ca,]
f3485e24d796c33f11048f74e447853ef4a6dc53c,]
f3050b5586ddfec5da0d719338a6afa8b166985bP,]
f1948a2d5dc8745f725e3ba0b24e14847778cb19&,]
f16c6ce0c7eabd4f5896962335879b3932138e52S,]
f06554b06ac49f129086c8889690faaa761398bb5-]f00e7c584731135892cb1bc133672a3d63d9e095<00>,]
eee4e109fd92ea679600a61dd7d3428efa786a64m,]
eecf3aaa6aadf48778bb1daa6b09d011632b-]a8c4718ce66e527a5fd1726e3aea5d6c8e33efff<00>-]855593c778f9f6c98a16afbd8e3097dbde09685c<00>-]8004558792c00764d173dc63c03d3a391acfe6b7<00>-]a5c83733c6abcd1a089bed36cf2ef38577ec5521<00>-]b68ff86ce8591931d3bef1294f8b46dae63780ad<00>,]
778e77ac46880d905d104d4f771fc5bb978a19ee},]
76eea8436996c7e9c8f7ad3dac34a12865edab249-]76e1cf37ae212298802799c2c3588030d20a769f<00>,]
76c0579c23504531220601029d455dca6413b628<-]765e049036ca947af05fb5b4f29b9daf4b363558<00>,]
763d0321ced31b774bd4ba2f9f369c087cbd278eW-]70882fa7790685902d4d8b56ba08a361f6e74eb1<00>-]703d0b290a4ece50c17854ed72ecc808ce3e6f43<00>,]
6e39523a0acd9855ff465598253c323f7dfd3cda-]6995ac2e570960403c02250b02e64cafed8378fd<00>-]6980e1e551cadbde62454bedf5e1324032fa1e40<00>-]6848895fe48b0ca3b0bc34c1bcdf66eb58e64308<00>-]67ea9f0fe38b6848de19578589eab498473562c3<00>,]
6718cc5cd4e1484990ee79a8c3cffaad6d7271c3,]
66401c00817c71713e86438385d91956246aeaabf,]
65d3575b1c380b1bcc14ec69ccf6989c04be9493Z,]
64832c7b1602f0922e4e818ad045d1bb5ae95dd6^-]614d66c63f8a04cf24cf19ce885f6a34be56a67c<00>,]
612b437425a8077a832c27b7f4ec057143e87a8cj,]
6125b966172dd6cde3563f2ae10d8f782d14e1de,]
5eb4500b8053ac8dd1a21bfca10c818e1e0a2405[-]c501a067498b94558da0e0510a4c29370388aee0<00>-]c2eec09d057ce3b7277395e6820f38744e67fb97<00>,]
c20baa16cb57ff4979569871d15294fa720bbc23O-]c1350b1680d30a7bdcb9837bff2e0e8c40f9a92a<00>-]c0f83a70b1c225e7705c301e1106332819bff375<00>,]
bde7543a8b3ce071342dfaea2a14357431d94b82M+]	bd9e0c2f5aaf68d784862ab361cc1a41fc9b32cd,]
bac41b59697da3ca5c80ca08f2bbbc97a3576248a,]
b8645fcfdf5af5759dc20ae769b96be510bdff1a)-]b7741ea891833418cc888b38f9f529bdb86409a4<00>-]b615e2186f1982009d863f3f2f98909f2f7815ab<00>,]
ac14e6bf50d1491043baf1d854727a68f5f3f51d,]
a9d9352d43986d4a5a3554a84b99580225ec00cf,]
a673b5ccb8fed1cb38edf75ead930569ba568c10z-]a659692ed5031c5410668d644a60d7806bb2efbb<00>,]
a2e89c6111f3e306c56472306795af290ffb29af,]
a2e4dc4b1cce765255e4d15084811da125c564c5R,]
9ed603d5743ef547a23578c5d50bd23069a6f2a8{,]
9d48eb6b89a9d7aa6feab3f6b2f57c70c1d9d18fw,]
9d2c1271f1219522d13f150c2b04123bef300dd9E,]
9aa8f3d1df6ff6d266a531432fe9ea0bb56ad3c3J-]997d371f1e063ff11e00fc6c0aef259558b92303<00>,]
993f5b0bb126caae848937b2323efabdf8bc21e9`,]
97edc89b0a19e90e2123f22315b88aaf7033bb3a~,]
973f17392cb7b417271e9d482d17a44a8c70c70a,]
95d36d171e5e2183c424f535fad2e8053f5cec64Y-]94e8fc6068b6dff5a2a688f51c44ebfdd23f7e1a<00>-]904014fb5cb22e8241c55e2fc6ae46288c5eebaf<00>,]
8eacd0f01ab0f53706561dda0ce8d1f96544a348p,]
8e1408e93d56b214a9018a7c13422715367a28bex,]
8de2fdb04edce612738eb51e14ecc426381f8ed8,,]
8b1d8d46836a6d5eb4355315b64d85c128cbff27$,]
892b955b6fb175c92f3f294ab431f97a8827748d8,]
87fbf4fa017a90b5ff819bcfca17fb52d6f6a790',]
87a6e1ec4dd1df928541467296e4cf2a0f2df0c3b,]
83cf2b3372ef98f7fa5caf94aa44e7262ee47519
-]802fed876e180f32c06ede4d1cc951ba44f79dd2<00>,]
7edaa9cc255ba8e0938cb563110b204a4f393d60-]7de4f6fddb11254d1fd5f8adfd67b6e0c9439eaa<00>,]
7d7de228c501ef486534cca1829378eef8ef1081G,]
78dec404a01664b35f3c740834597920186fbba7u,]
78c295cfd7469cd3d494a48df7bd7748139e0660
<00>
<0A>
<0B>
<EFBFBD>	<09><08>U<06><05><04><03>?<00>
<01><00>v]<5D>+1<>#GG
p5ac2852c69cc7bda25677129da011dec23fc3d77making-a-fast-curry-push-enter-versus-eval-apply-for-higher-order-languages.pdflanguages/haskell/making a fast curry push enter versus eval apply for higher order languages2017-09-11T23:06:10.5060729982017-09-11T23:06:10.506072998<EFBFBD>]w]<5D>m1<6D>eGG
n9d48eb6b89a9d7aa6feab3f6b2f57c70c1d9d18ftackling-the-awkward-squad-monadic-input-output-concurrency-exceptions-and-foreign-language-calls-in-haskell.pdflanguages/haskell/tackling the awkward squad monadic input output concurrency exceptions and foreign language calls in haskell2017-09-11T23:06:10.5499750982017-09-11T23:06:10.549975098<EFBFBD>=u	]O1GGG
m78dec404a01664b35f3c740834597920186fbba7a-poor-mans-concurrency-monad.pdflanguages/haskell/a poor mans concurrency monad2017-09-11T23:06:10.3302910162017-09-11T23:06:10.330291016<EFBFBD>[t	]m1eGG<00>2128052ca0319cdf9c9256eb52f26a23c6527094a-practical-optional-type-system-for-clojure.pdflanguages/clojure/a practical optional type system for clojure2017-09-11T23:06:10.3228588872017-09-11T23:06:10.322858887<EFBFBD>Xs	]k3cEE
o0404bd58e5f1edbd288cd69fcbc224485af415bfa-mathematical-theory-of-communication-1948.pdfinformation_theory/a mathematical theory of communication 19482017-09-11T23:06:10.315979982017-09-11T23:06:10.31597998<EFBFBD>vr
]<5D>9{GG
le36073e9e5c97e0204050c0c316d87479f94974ethe-pagerank-citation-ranking-bringing-order-to-the-web.pdfinformation_retrieval/the pagerank citation ranking bringing order to the web2017-09-11T23:06:10.3003291022017-09-11T23:06:10.300329102<EFBFBD>!q	]19)EE<00>016f4930ad10f8097c42e5294b56d25bfb3c121fokapi-at-trec3.pdfinformation_retrieval/okapi at trec32017-09-11T23:06:10.275385012017-09-11T23:06:10.27538501<EFBFBD>7p	]E9=GG<00>8eacd0f01ab0f53706561dda0ce8d1f96544a348graph_of_word_and_tw_idf.pdfinformation_retrieval/graph of word and tw idf2017-09-11T23:06:10.2680969242017-09-11T23:06:10.268096924<EFBFBD>ko	]y9qGG<00>da731f99e05dd4f1fad1d21a1c6124efeb3bcf61authoritative-sources-in-a-hyperlinked-environment.pdfinformation_retrieval/authoritative sources in a hyperlinked environment2017-09-11T23:06:10.2016918952017-09-11T23:06:10.201691895<EFBFBD>>n	]O3GGG
k18a74ae5e33b76a0528d0724d5c55a98dabe0b1fthe_lisp_ii_garbage_collector.pdfgarbage_collection/the lisp ii garbage collector2017-09-11T23:06:10.1830480962017-09-11T23:06:10.183048096<EFBFBD> m]<5D>/3<>'GG<00>eee4e109fd92ea679600a61dd7d3428efa786a64parallel_generational_copying_garbage_collection_with_a_block_structured_heap.pdfgarbage_collection/parallel generational copying garbage collection with a block structured heap2017-09-11T23:06:10.0999919432017-09-11T23:06:10.099991943<EFBFBD>l]<5D>3<>GG<00>158d08ec7c2134382e20b44001903ad5b8a521b2incremental_mature_garbage_collection_using_the_train_algorithm.pdfgarbage_collection/incremental mature garbage collection using the train algorithm2017-09-11T23:06:09.6336560062017-09-11T23:06:09.633656006<EFBFBD>,k]<5D>A'<27>9GG
j5b0ccfcd8135c9599f8088443ed7de1874fa1c97why-students-engage-in-gaming-the-system-behavior-in-interactive-learning-environments.pdfgamification/why students engage in gaming the system behavior in interactive learning environments2017-09-11T23:06:09.5316699222017-09-11T23:06:09.531669922<EFBFBD>Xj	]o'gGG
h612b437425a8077a832c27b7f4ec057143e87a8cgamification-in-education-what-how-why-bother.pdfgamification/gamification in education what how why bother2017-09-11T23:06:09.5095869142017-09-11T23:06:09.509586914<EFBFBD>i]<5D>A<>
EE<00>2db53cdcf4ba7c67321c022954c2b2be9c8a40bda-theoreticians-guide-to-the-experimental-analysis-of-algorithms.pdfexperimental_algorithmics/a theoreticians guide to the experimental analysis of algorithms2017-09-11T23:06:09.394502932017-09-11T23:06:09.39450293<EFBFBD>}h]<5D>5<>GG
ed0cb011908e333fe17309518249be05820b5239fzookeeper-wait-free-coordination-for-internet-scale-systems.pdfdistributed_systems/zookeeper wait free coordination for internet scale systems2017-09-11T23:06:09.2425061042017-09-11T23:06:09.242506104
4p
<0A><0C><0B>
f	<09><08><07><06>O<05><04><03>'
s<00><00>3<EFBFBD>		]E1=GG
~6980e1e551cadbde62454bedf5e1324032fa1e40unix-time-sharing-system.pdfoperating_systems/unix time sharing system2017-09-11T23:06:12.6897451172017-09-11T23:06:12.689745117<EFBFBD><0F>	]!1GG
zf00e7c584731135892cb1bc133672a3d63d9e095therac.pdfoperating_systems/therac2017-09-11T23:06:12.6663500982017-09-11T23:06:12.666350098<EFBFBD><1D>]<5D>/1<>'EE<00>4b85765a808e4c29f05bc48a17a2dced1702db9dsolaris-zones-operating-system-support-for-consolidating-commercial-workloads.pdfoperating_systems/solaris zones operating system support for consolidating commercial workloads2017-09-11T23:06:12.608392092017-09-11T23:06:12.60839209<EFBFBD>G<EFBFBD>	]Y1QGG
|d4723308389e064389bc4e6aee46db5fc9b214eelive-migration-of-virtual-machines.pdfoperating_systems/live migration of virtual machines2017-09-11T23:06:12.3678010252017-09-11T23:06:12.367801025<EFBFBD>G<EFBFBD>	]Y1QGG
{765e049036ca947af05fb5b4f29b9daf4b363558kvm-linux-virtual-machines-monitor.pdfoperating_systems/kvm linux virtual machines monitor2017-09-11T23:06:12.0644060062017-09-11T23:06:12.064406006<EFBFBD>K<EFBFBD>	]]1UGG<00>a659692ed5031c5410668d644a60d7806bb2efbbjails-confining-the-omnipotent-root..pdfoperating_systems/jails confining the omnipotent root.2017-09-11T23:06:11.9372780762017-09-11T23:06:11.937278076<EFBFBD>?<3F>	]K=CGG<00>c2eec09d057ce3b7277395e6820f38744e67fb97efficient-lock-free-b+trees.pdfnon_blocking_algorithms/efficient lock free b+trees2017-09-11T23:06:11.7259489752017-09-11T23:06:11.725948975<EFBFBD>+<2B>	]7=/GG
y6995ac2e570960403c02250b02e64cafed8378fda-wait-free-stack.pdfnon_blocking_algorithms/a wait free stack2017-09-11T23:06:11.3879260252017-09-11T23:06:11.387926025<EFBFBD>]<5D>
	]i=aGG<00>d5c3b8b3006fc4b24e770f028c938d4bcbd62695a-wait-free-queue-as-fast-as-fetch-and-add.pdfnon_blocking_algorithms/a wait free queue as fast as fetch and add2017-09-11T23:06:11.3326069342017-09-11T23:06:11.332606934<EFBFBD><0F>]<5D>1<>GG<00>802fed876e180f32c06ede4d1cc951ba44f79dd2scatteralloc-massively-parallel-dynamic-memory-allocation-for-the-gpu.pdfmemory_management/scatteralloc massively parallel dynamic memory allocation for the gpu2017-09-11T23:06:10.9212509772017-09-11T23:06:10.921250977<EFBFBD>K	]]1UGG
w381c0200a69d43c6605079aaf73beace048b76a6making-lockless-synchronization-fast.pdfmemory_management/making lockless synchronization fast2017-09-11T23:06:10.8874990232017-09-11T23:06:10.887499023<EFBFBD>#~	];%3GG
t97edc89b0a19e90e2123f22315b88aaf7033bb3atranscendence-of-pi.pdfmathematics/transcendence of pi2017-09-11T23:06:10.8822609862017-09-11T23:06:10.882260986<EFBFBD>7}]<5D>/a<>'GG
v778e77ac46880d905d104d4f771fc5bb978a19eetoward-a-unified-theory-of-sparse-dimensionality-reduction-in-euclidean-space.pdfmachine_learning/dimensionality_reduction/toward a unified theory of sparse dimensionality reduction in euclidean space2017-09-11T23:06:10.8137690432017-09-11T23:06:10.813769043<EFBFBD>k|	]ea]GG
u4ba0079fbfaf8a49f36f4e400f44c17b7f4552d4a-sparse-johnson-lindenstrauss-transform.pdfmachine_learning/dimensionality_reduction/a sparse johnson lindenstrauss transform2017-09-11T23:06:10.7901140142017-09-11T23:06:10.790114014<EFBFBD>{]<5D>9<>	GG
q9ed603d5743ef547a23578c5d50bd23069a6f2a8representing-game-dialogue-as-expressions-in-first-order-logic.pdflogic_and_programming/representing game dialogue as expressions in first order logic2017-09-11T23:06:10.7235681152017-09-11T23:06:10.723568115<EFBFBD>Wz	]e9]GG
xa673b5ccb8fed1cb38edf75ead930569ba568c10on-the-meanings-of-the-logical-constants.pdflogic_and_programming/on the meanings of the logical constants2017-09-11T23:06:10.7168100592017-09-11T23:06:10.716810059<EFBFBD>Ay	]Q5IGG
sd25c77b7d5f4b6742e63bc6f3b92ab220c833d23The-Early-History-Of-Smalltalk.pdflanguages/smalltalk/the early history of smalltalk2017-09-11T23:06:10.6869809572017-09-11T23:06:10.686980957<EFBFBD>Ix	]Y5QGG
r8e1408e93d56b214a9018a7c13422715367a28beDesign-Principles-Behind-Smalltalk.pdflanguages/smalltalk/design principles behind smalltalk2017-09-11T23:06:10.6670510252017-09-11T23:06:10.667051025
<03><00>m<0E>
<0A><0C><0B>
<EFBFBD>	<09>
<01>	<02>`V<06><00><05><00><19>]<5D>a<>	GG
<01>223b694fb70d4bd18ba0f4bd73ff3c6bc8f6370aray-integrating-rx-and-async-for-direct-style-reactive-streams.pdfparadigms/functional_reactive_programming/ray integrating rx and async for direct style reactive streams2017-09-11T23:06:13.0470969242017-09-11T23:06:13.047096924<EFBFBD>X<EFBFBD>	][OSGG<00>f6dce666a0f64f97f380f99cba7f14e24d5f54adorganizing-programs-without-classes.pdfparadigms/functional_programming/organizing programs without classes2017-09-11T23:06:12.9792910162017-09-11T23:06:12.979291016<EFBFBD>q<EFBFBD>	]kacGG
<01>5046034fe0cddda681ad9374d306fd27eec8b5fba-survey-of-functional-reactive-programming.pdfparadigms/functional_reactive_programming/a survey of functional reactive programming2017-09-11T23:06:12.9885161132017-09-11T23:06:12.988516113?
<01>
]<5D>=GGeb654b2087706468fe3173c4b38b940be0c85722cognitive-computing-programming-paradigm-corelet-language.pdfparadigms/new_paradigms/cognitive computing programming paradigm corelet language2017-09-11T23:06:13.0537729492017-09-11T23:06:13.053772949?
<01>]<5D>a<>	GG223b694fb70d4bd18ba0f4bd73ff3c6bc8f6370aray-integrating-rx-and-async-for-direct-style-reactive-streams.pdfparadigms/functional_reactive_programming/ray integrating rx and async for direct style reactiv<69>|<7C>
]<5D>=GG
<01>eb654b2087706468fe3173c4b38b940be0c85722cognitive-computing-programming-paradigm-corelet-language.pdfparadigms/new_paradigms/cognitive computing programming paradigm corelet language2017-09-11T23:06:13.0537729492017-09-11T23:06:13.053772949<EFBFBD>U<EFBFBD>	]OaGGG
<01>e306d45aeb2d3f72055ce72ccbebd0ccb42cdf17functional-reactive-animation.pdfparadigms/functional_reactive_programming/functional reactive animation2017-09-11T23:06:13.0229680182017-09-11T23:06:13.022968018<EFBFBD>[<5B>	]UaMGG
<01>d7341e40b11008965d60631953ad83e89aa40584deprecating-the observer-pattern.pdfparadigms/functional_reactive_programming/deprecating the observer pattern2017-09-11T23:06:12.9958210452017-09-11T23:06:12.995821045	]YOQGGc501a06749<34>=<3D>	]7a/GG
<01>09ac606ba306a1bea91642deb2af0909360b038ffrp-in-plt-scheme.pdfparadigms/functional_reactive_programming/frp in plt scheme2017-09-11T23:06:13.0173220212017-09-11T23:06:13.017322021<EFBFBD>V<EFBFBD>	]YOQGG
<01>c501a067498b94558da0e0510a4c29370388aee0why-functional-programming-matters.pdfparadigms/functional_programming/why functional programming matters2017-09-11T23:06:12.9834589842017-09-11T23:06:12.983458984<EFBFBD>d<EFBFBD>	]gO_GG
<01>59776eb2358b4be265e7dae9df4f946dab25bf6foptimal-purely-functional-priority-queues.pdfparadigms/functional_programming/optimal purely functional priority queues2017-09-11T23:06:12.9515539552017-09-11T23:06:12.951553955<EFBFBD><1A>
]<5D>O<>GG
}fec6b29569eac1a340990bb07e90355efd2434ecfunctional-programming-with-bananas-lenses-envelops-and-barbed-wire.pdfparadigms/functional_programming/functional programming with bananas lenses envelops and barbed wire2017-09-11T23:06:12.9420480962017-09-11T23:06:12.942048096<EFBFBD>X<EFBFBD>	][OSGG
<01>904014fb5cb22e8241c55e2fc6ae46288c5eebafequal-rights-for-functional-objects.pdfparadigms/functional_programming/equal rights for functional objects2017-09-11T23:06:12.9332219242017-09-11T23:06:12.933221924<EFBFBD>r<EFBFBD>	]uOmGG
d238ce802f284a57bffb618af93d009457b8320bconcatenative-programming-an-overlooked-paradigm.pdfparadigms/functional_programming/concatenative programming an overlooked paradigm2017-09-11T23:06:12.8906689452017-09-11T23:06:12.890668945<EFBFBD>i<EFBFBD>
	]uAmEE
<01>30baa244b66e81d737ccf9f667c9bfca4f0c18f1common-ground-and-coordination-in-joint-activity.pdforganizational_simulation/common ground and coordination in joint activity2017-09-11T23:06:12.787232912017-09-11T23:06:12.78723291<EFBFBD>3<EFBFBD>		]E1=GG
~6980e1e551cadbde62454bedf5e1324032fa1e40unix-time-sharing-system.pdfoperating_systems/unix time sharing system2017-09-11T23:06:12.6897451172017-09-11T23:06:12.689745117<EFBFBD><0F>	]!1GG
zf00e7c584731135892cb1bc133672a3d63d9e095therac.pdfoperating_systems/therac2017-09-11T23:06:12.6663500982017-09-11T23:06:12.666350098
<04>
<01>e
<01><05>#<02>S%R
q<04><08><0B><0C>r
<01>
Q<00>J<EFBFBD>/	]g_GGdd0854bf535d79d51104ae3d5c19c6ac7e562180macaroons-cookies-with-contextual-caveats.pdfsecurity/macaroons cookies with contextual caveats2017-09-11T23:06:14.4265568852017-09-11T23:06:14.426556885<EFBFBD>,<2C>.	]IAGG67ea9f0fe38b6848de19578589eab498473562c3ids-evasion-ptacek-newsham.pdfsecurity/ids evasion ptacek newsham2017-09<30>`<60>	]s/kGG
<01>d62e2ae46b1cfac38357e6ce32bad7b36b0b49b4extensible-pattern-matching-extensible-language.pdfpattern_matching/extensible pattern matching extensible language2017-09-11T23:06:13.2372028812017-09-11T23:06:13.237202881<EFBFBD>a<EFBFBD>	]}uGG
<01>b7741ea891833418cc888b38f9f529bdb86409a4on-the-attraction-of-two-perfectly-conducting-plates.pdfphysics/on the attraction of two perfectly conducting plates2017-09-11T23:06:13.2988210452017-09-11T23:06:13.298821045<EFBFBD>:<3A>	]M/EGG
<01>3547ac839d02f6efe3f6f76a8289738a22528442aho-corasick-string-matching.pdfpattern_matching/aho corasick string matching2017-09-11T23:06:13.1525471192017-09-11T23:06:13.152547119<EFBFBD><1D>	]91GG
<01>30ef9946a1733c097d541ffaae8e95f0af862a08buridans-principle.pdfphysics/buridans principle2017-09-11T23:06:13.2931608892017-09-11T23:06:13.293160889.	]O/GEE997d371f1e063ff11e00fc6c0aef25955<35><1F>!	]?7GG<00>70882fa7790685902d4d8b56ba08a361f6e74eb1predicate-dispatching.pdfplt/predicate dispatching2017-09-11T23:06:13.7644509282017-09-11T23:06:13.764450928<EFBFBD>:<3A>	]O/GEE
<01>997d371f1e063ff11e00fc6c0aef259558b92303warnings-for-pattern-matching.pdfpattern_matching/warnings for pattern matching2017-09-11T23:06:13.242854982017-09-11T23:06:13.24285498<EFBFBD>E<EFBFBD>	]c[EE
<01>07ad71a8d82bf51e0b5d1d892aa6a10673a3b830on-the-electrodynamics-of-moving-bodies.pdfphysics/on the electrodynamics of moving bodies2017-09-11T23:06:13.516997072017-09-11T23:06:13.51699707<EFBFBD>d<EFBFBD>	]w/oGG<00>6848895fe48b0ca3b0bc34c1bcdf66eb58e64308compiling-pattern-matching-to-good-decision-trees.pdfpattern_matching/compiling pattern matching to good decision trees2017-09-11T23:06:13.2295769042017-09-11T23:06:13.229576904	z<00>	]?7GGc0f83a70b1c225e7705c301e1106332819bff375propositions-as-types.pdfplt/propositions as types2017-09-11T23:06:13.8390410162017-09-11T23:06:13.839041016<EFBFBD>Q<EFBFBD>"	]qiGG<00>76e1cf37ae212298802799c2c3588030d20a769fprincipal-type-schemes-for-functional-programs.pdfplt/principal type schemes for functional programs2017-09-11T23:06:13.7899331052017-09-11T23:06:13.789933105
<01>	]}uGG557b1ec3182ccb3a902cc9904a443accb438842fprogramming-languages-application-and-interpretation.pdfplt/programming languages application and interpretation2017-09-11T23:06:13.7966269532017-09-11T23:06:13.796626953A	]qiGG76e1cf37ae212298802799c2c3588030d20a769fprincipal-type-schemes-for-functional-programs.pdfplt/principal type schemes for functional programs2017-09-11T23:06:13.7899331052017-09<30><1F>%	]?7GG
<01>c0f83a70b1c225e7705c301e1106332819bff375propositions-as-types.pdfplt/propositions as types2017-09-11T23:06:13.8390410162017-09-11T23:06:13.839041016<EFBFBD>]<5D>#	]}uGG<00>557b1ec3182ccb3a902cc9904a443accb438842fprogramming-languages-application-and-interpretation.pdfplt/programming languages application and interpretation2017-09-11T23:06:13.7966269532017-09-11T23:06:13.796626953<EFBFBD>S<EFBFBD>$	]skGG
<01>b615e2186f1982009d863f3f2f98909f2f7815abprogramming-with-algebraic-effects-and-handlers.pdfplt/programming with algebraic effects and handlers2017-09-11T23:06:13.8081340332017-09-11T23:06:13.808134033<EFBFBD>]<5D> 	]}uGG<00>c1350b1680d30a7bdcb9837bff2e0e8c40f9a92aon-understanding-types-data-abstract
.<07><0F><0F>yL<0E><0E><0E>h:

<0A>
<0A>
<0A>
W
*c<0C><0C><0C>tG<0B><0B><0B><07>d7

<EFBFBD>
<EFBFBD>
<EFBFBD>
U
(	<09>5	<09>	<09>	s	F	<08><08><08>-]eaf3b1c41b5cc8bc329206a175dc5149341615d1<00>-]f55238913918c61b0dad87974699d05a5d71e709<00>-]f4b381f4482586dbdd15fc92bee81ce68bcb6898<00>-]dd0854bf535d79d51104ae3d5c19c6ac7e562180<00>-]fec6b29569eac1a340990bb07e90355efd2434ec<00>,]
fe0ae75e97abe2686e6bc8cbe94bfd08934e36da,]
fd443b2ce70c48202ba26cbc6caa471ae262e270@,]
fc11031895c302dc52404d34de58af1a72f3b817g,]
fb2db075fa0230289a4f05caf2127b95fcc9aa9c
-]f6dce666a0f64f97f380f99cba7f14e24d5f54ad<00>,]
f52e7afce70597024c3be7df105185dd59a2c8e6A,]
f5222809526d8a419a1752547880ba0a9013a8ca,]
f3485e24d796c33f11048f74e447853ef4a6dc53c,]
f3050b5586ddfec5da0d719338a6afa8b166985bP,]
f1948a2d5dc8745f725e3ba0b24e14847778cb19&,]
f16c6ce0c7eabd4f5896962335879b3932138e52S,]
f06554b06ac49f129086c8889690faaa761398bb5-]f00e7c584731135892cb1bc133672a3d63d9e095<00>,]
eee4e109fd92ea679600a61dd7d3428efa786a64m,]
eecf3aaa6aadf48778bb1daa6b09d011632b9f55*-]eb654b2087706468fe3173c4b38b940be0c85722<00>,]
e95ecb39639ce118c7ddd5bd7892378eacdd105f!,]
e76af50e96b12fc507e73b025fe9da4a99600af9,]
e51582689653f238029d984cd1780c93ef672771/-]e437aad09eb0508f015c4615e3a9c738bdee9fdf<00>,]
e36073e9e5c97e0204050c0c316d87479f94974er-]e306d45aeb2d3f72055ce72ccbebd0ccb42cdf17<00>,]
e2e60f19214efaa7d842b4a3b3b322964bf78dc7,]
e1ac8e8d810a148dc3f5291795b0ac0b114db824_-]e186a8489dc6ab1c5dd30fc0501f7866d0c3d0f1<00>,]
daf38d927e2b21c885efdb4b2cc46a2d9f47d679:,]
da731f99e05dd4f1fad1d21a1c6124efeb3bcf61o-]d7341e40b11008965d60631953ad83e89aa40584<00>,]
d65e79756ac6817d4780286045a35d34aaaaf836=-]d62e2ae46b1cfac38357e6ce32bad7b36b0b49b4<00>,]
d62de5f995164fff50f5ce61c0113f6bc9f04225-]d5c3b8b3006fc4b24e770f028c938d4bcbd62695<00>-]d4723308389e064389bc4e6aee46db5fc9b214ee<00>,]
d25c77b7d5f4b6742e63bc6f3b92ab220c833d23y-]d238ce802f284a57bffb618af93d009457b8320b<00>,]
d14dee375bc275d08b09e5b7d420c28a5ef6b47a]-]d0d8b7501d7f75613d5493d706d6d81852a73d6e<00>,]
d0cb011908e333fe17309518249be05820b5239fh,]
ce8411564f95396b503868217469e2aaf1b996c9,]
cb4710f77feed90ae01b332c492853a5b20e2c7d ,]
ca9ccbcf4a8440590a81f94295a22386a422d198\
9
K	<09><0E>
<0B>
<EFBFBD><0C><08>q<06><05>K<00>)<29><	];53GG272ef349f3b3561588a87a070de802c3c0246394affective-computing.pdfaffective-computing/affective computing2018-02-02T06:25:06.4023759772018-02-02T06:25:06.402375977<EFBFBD>e<EFBFBD>;	]w5oGGa8c4718ce66e527a5fd1726e3aea5d6c8e33efffTheories-Methods-and-Current-Research-on-Emotions.pdfaffective-computing/theories methods and current research on emotions2018-01-30T06:25:06.1424230962018-01-30T06:25:06.142423096<EFBFBD><0C>:	]#+GG855593c778f9f6c98a16afbd8e3097dbde09685cmarsyas.pdfaudio_comp_sci/marsyas2017-10-27T05:25:06.0209260252017-10-27T05:25:06.020926025<EFBFBD><0E>9	]%+GGeaf3b1c41b5cc8bc329206a175dc5149341615d1essentia.pdfaudio_comp_sci/essentia2017-10-26T05:25:05.5868701172017-10-26T05:25:05.586870117<EFBFBD>.<2E>8	]G+?EE472f436ad317b23d7bd1ad53fcb4f23e8f0997a7real-time-chord-detection.pdfaudio_comp_sci/real time chord detection2017-10-25T05:25:06.011989992017-10-25T05:25:06.01198999<EFBFBD>P<EFBFBD>7	]WOOEE16c8ad89060897e39803a175470d7990bd40cd2bpurely-functional-data-structures.pdfparadigms/functional_programming/purely functional data structures2017-10-20T05:25:05.914747072017-10-20T05:25:05.91474707<EFBFBD>,<2C>0	]G?GG
<01>b68ff86ce8591931d3bef1294f8b46dae63780adsok-eternal-war-in-memory.pdfsecurity/sok eternal war in memory2017-09-11T23:06:14.8241650392017-09-11T23:06:14.824165039<0B><00>	]#%GG59a968fa431e7117aa11005ed98ab39f1efddc30ts-asap.pdftime_series/ts asap2017-09-11T23:06:15.0964880372017-09-11T23:06:15.0964880<EFBFBD>I<EFBFBD>5	]a%YGG
1396a6cd134a7f41eeb1e5d4ca8d4edf6edfc432operators-on-inhomogeneous-time-series.pdftime_series/operators on inhomogeneous time series2017-09-11T23:06:15.0884909672017-09-11T23:06:15.088490967	]g1_GG8004558792<39>U<EFBFBD>4	]g1_GG
8004558792c00764d173dc63c03d3a391acfe6b7systematic-review-in-software-engineering.pdfsystematic_review/systematic review in software engineering2017-09-11T23:06:15.0225739752017-09-11T23:06:15.022573975<EFBFBD><0B>6	]#%GG
<01>59a968fa431e7117aa11005ed98ab39f1efddc30ts-asap.pdftime_series/ts asap2017-09-11T23:06:15.0964880372017-09-11T23:06:15.096488037<EFBFBD><02>3]<5D>7<>GG
f55238913918c61b0dad87974699d05a5d71e709An-Elementary-Proof-of-a-Theorem-of-Johnson-and-Lindenstrauss.pdfsublinear_algorithms/an elementary proof of a theorem of johnson and lindenstrauss2017-09-11T23:06:15.0059938962017-09-11T23:06:15.005993896<EFBFBD>N<EFBFBD>2	]]7UGG
<01>a5c83733c6abcd1a089bed36cf2ef38577ec55211985-Flajolet-Probabilistic-counting.pdfsublinear_algorithms/1985 flajolet probabilistic counting2017-09-11T23:06:14.9164609382017-09-11T23:06:14.916460938<EFBFBD><14>1]<5D>%/<2F>GG
<01>f4b381f4482586dbdd15fc92bee81ce68bcb68982014-ssac-pointwise-predicting-points-and-valuing-decisions-in-real-time.pdfsports_analytics/2014 ssac pointwise predicting points and valuing decisions in real time2017-09-11T23:06:14.8365629882017-09-11T23:06:14.836562988
<00>/l
m<0C><0B>
)	p<08><07>Y<05><04>7~<02>
<01>
<00><00>T
<01><17>'GGhttp://www.cs.duke.edu/courses/cps296.4/spring04/papers/Adleman94.pdfMolecular Computation of Solutions to Combinatorial Problemsbiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949z	
M'GGhttp://en.wikipedia.org/wiki/Pcrwikipediabiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949<EFBFBD>F

a<>+GGhttps://github.com/ibab/tensorflow-wavenet[Python] Implementation with the TensorFlow Machine Intelligence libraryaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>7

W<>	+GGhttps://github.com/basveeling/wavenet[Python] Implementation with the Keras Neural Networks libraryaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>6

<01>W+GGhttps://deepmind.com/blog/wavenet-generative-model-raw-audio/Announcement and interactive examplesaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD> 	
U_+GGhttps://arxiv.org/pdf/1609.03499.pdfWaveNet: A Generative Model for Raw Audioaudio_comp_sci/2017-09-11T23:06:15.2434069822017-09-11T23:06:15.243406982<EFBFBD>;
	
e[UGG
http://ftp.cs.ucla.edu/pub/stat_ser/r360.pdfThe algorithmization of counterfactualsartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>>	
mYUGGhttp://ftp.cs.ucla.edu/pub/stat_ser/R218-B-L.pdfCausal diagrams for empirical researchartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>:	
uIUGGhttp://ftp.cs.ucla.edu/pub/stat_ser/r156-reprint.pdfA theory of inferred causationartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>[

	c<>UGGhttp://ftp.cs.ucla.edu/pub/stat_ser/r30.pdfReverend Bayes on inference engines: A distributed hierarchical approachartificial_intelligence/judea_pearl/2017-09-11T23:06:15.2420400392017-09-11T23:06:15.242040039<EFBFBD>j	
<01>!<21>=GG
http://airesearch.com/wp-content/uploads/2016/01/deepmind-mastering-go.pdfMastering the Game of Go with Deep Neural Networks and Tree Searchartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>	
W#=GGhttp://bayes.cs.ucla.edu/jp_home.htmlJudea Pearlartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>6	
yU=GGhttp://www.csee.umbc.edu/courses/471/papers/turing.pdfComputing Machinery and Intelligenceartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>T
<01><0B>{=GGhttps://github.com/papers-we-love/papers-we-love/blob/master/artificial_intelligence/3-bayesian-network-inference-algorithm.pdfAnalysis of Three Bayesian Network Inference Algorithms: Variable Elimination, Likelihood Weighting, and Gibbs Samplingartificial_intelligence/2017-09-11T23:06:15.2211870122017-09-11T23:06:15.221187012<EFBFBD>
<01>'<27>Q#GG	https://www.ics.uci.edu/~fielding/pubs/dissertation/fielding_dissertation.pdfArchitectural Styles and the Design of Network-based Software Architectures (REST) by Roy Fieldingapi_design/2017-09-11T23:06:15.1943510742017-09-11T23:06:15.194351074<EFBFBD>g

g<>gGGhttp://www.bodden.de/pubs/far+14flowdroid.pdfFlowDroid: Precise Context, Flow, Field, Object-sensitive and Lifecycle-aware Taint Analysis for Android Appsandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>|

u<>GGhttp://www.cse.psu.edu/~duo114/pubs/octeau-sec13.pdfEffective Inter-Component Communication Mapping in Android with Epicc: An Essential Step Towards Holistic Security Analysisandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>@

<01>uGGhttps://www.eecs.berkeley.edu/~daw/papers/intents-mobisys11.pdfAnalyzing Inter-Application Communication in Androidandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959<EFBFBD>N


<01>+qGGhttp://blog.sei.cmu.edu/post.cfm/secure-coding-tools-analyzing-android-apps-118Two Secure Coding Tools for Analyzing Android Appsandroid/2017-09-11T23:06:15.1916579592017-09-11T23:06:15.191657959
/I<0E>
f<0C><0B>
<EFBFBD>
	"(
@W<04><03>/3
k<00>|#	
A%1GG)http://gigavoxels.imag.fr/Project pagecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>;&

<01>)91GG(http://www.cs.rpi.edu/~cutler/classes/advancedgraphics/S08/lectures/kajiya.pdfThe Rendering Equationcomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>E%

<01>e1GG"http://www.cs.northwestern.edu/~ago820/cs395/Papers/Phong_1975.pdfIllumination for computer generated picturescomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>Z$

<01>IW1GG!http://page.mi.fu-berlin.de/block/htw-lehre/wise2015_2016/bel_und_rend/skripte/gouraud1971.pdfContinuous shading of curved surfacescomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>"	
q1GG'http://maverick.inria.fr/Publications/2009/CNLE09/Web pagecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>`!
<01><05>%1GGhttp://maverick.inria.fr/Publications/2009/CNLE09/CNLE09.pdfGigaVoxels : Ray-Guided Streaming for Efficient and Detailed Voxel Renderingcomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>N 

<01>o1GG https://www.cs.drexel.edu/~david/Classes/CS586/Papers/p343-whitted.pdfAn Improved Illumination Model for Shaded Displaycomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>f
<01><13>#1GGhttp://graphics.stanford.edu/papers/stabilization/karpenko_gyro.pdfDigital Video Stabilization and Rolling Shutter Correction using Gyroscopescomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>J

a<>9GGhttp://barroso.org/publications/isca00.pdfPiranha: A Scalable Architecture Based on Single-Chip Multiprocessingcomputer_architecture/2017-09-11T23:06:15.3536550292017-09-11T23:06:15.353655029<EFBFBD>
<01>w<EFBFBD>?GGhttps://www.researchgate.net/publication/220080099_MEXICA_A_computer_model_of_a_cognitive_account_of_creative_writingMEXICA: a computer model of a cognitive account of creative writing.computational_creativity/2017-09-11T23:06:15.3451440432017-09-11T23:06:15.345144043<EFBFBD>w

<01>UiQEEhttp://www.ams.org/journals/tran/1965-117-00/S0002-9947-1965-0170805-7/S0002-9947-1965-0170805-7.pdfOn the Computational Complexity of Algorithimscomp_sci_fundamentals_and_history/2017-09-11T23:06:15.321489992017-09-11T23:06:15.32148999<EFBFBD>_

e<>)QEEhttp://www.turingarchive.org/browse.php/B/12Turing, On computable numbers, with an application to the Entscheidungsproblemcomp_sci_fundamentals_and_history/2017-09-11T23:06:15.321489992017-09-11T23:06:15.32148999<EFBFBD>l

<>)QEEhttps://www.cs.virginia.edu/~robins/Turing_Paper_1936.pdfTuring, On computable numbers, with an application to the Entscheidungsproblemcomp_sci_fundamentals_and_history/2017-09-11T23:06:15.321489992017-09-11T23:06:15.32148999<EFBFBD>a

<01>;k9GGhttp://gatekeeper.dec.com/ftp/pub/dec/SRC/publications/broder/positano-final-wpnums.pdfOn the resemblance and containment of documentsclustering_algorithms/2017-09-11T23:06:15.3145280762017-09-11T23:06:15.314528076<EFBFBD>K
<01><0F>GGhttp://adam.chlipala.net/papers/SqlcachePOPL17/SqlcachePOPL17.pdfA Program Optimization for Automatic Database Result Cachingcaching/2017-09-11T23:06:15.2910549322017-09-11T23:06:15.291054932<EFBFBD>>

Y<>#GGhttp://www.vldb.org/conf/1994/P439.PDF2Q: A Low Overhead High Performance Buffer Management Replacement Algorithmcaching/2017-09-11T23:06:15.2910549322017-09-11T23:06:15.291054932<EFBFBD>
<01>%<25>
GGhttps://github.com/papers-we-love/papers-we-love/blob/master/caching/a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdfAn O(1) algorithm for implementing the LFU cache eviction schemecaching/2017-09-11T23:06:15.2910549322017-09-11T23:06:15.291054932<EFBFBD>C

<01>)S'GGhttps://homes.cs.washington.edu/~luisceze/publications/dnastorage-asplos16.pdfA DNA-Based Archival Storage Systembiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949<EFBFBD>4

<01>S'GGhttp://www.dna.caltech.edu/courses/cs191/paperscs191/turing.pdfThe chemical basis of morphogenesisbiocomputing/2017-09-11T23:06:15.2661479492017-09-11T23:06:15.266147949
<00>D<0E>
<0A><0C><<0B>
<EFBFBD>
	0S<07><06>#Q<04><03><02>C
l<00><00>\:
<01>!<21>
%GG>http://research.microsoft.com/en-us/um/people/lamport/pubs/time-clocks.pdfTime, Clocks, and the Ordering of Events in a Distributed Systemconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>T9

q<>/%GG6http://sigops.org/sosp/sosp13/papers/p33-david.pdfEverything You Always Wanted to Know About Synchronization but Were Afraid to Askconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>88	
os-GG5http://www.sci.utah.edu/~bsumma/projects/weaving/Panorama Weaving:
Fast and Flexible Seam Processingcomputer_vision/2017-09-11T23:06:15.4028640142017-09-11T23:06:15.402864014<EFBFBD>b7

<01>As-GG4http://www.disneyresearch.com/project/high-quality-single-shot-capture-of-facial-geometry/High-Quality Single-Shot Capture of Facial Geometrycomputer_vision/2017-09-11T23:06:15.4028640142017-09-11T23:06:15.402864014<EFBFBD>l6

<01>K}-GG3http://www.disneyresearch.com/project/coupled-3d-reconstruction-of-sparse-facial-hair-and-skin/Coupled 3D Reconstruction of Sparse Facial Hair and Skincomputer_vision/2017-09-11T23:06:15.4028640142017-09-11T23:06:15.402864014}5	=-1GGhttp://shapegrammar.org/shapegrammar.orgcomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>O4

k<>1GG/http://shapegrammar.org/ifip/SGBestPapers72.pdfShape Grammars and the Generative Specification of Painting and Sculpturecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>D3	
w1GG1http://cs.brown.edu/courses/csci2370/2000/1999/cabral.pdfImaging Vector Fields Using Line Integral Convolutioncomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>"2

<01>!1GG-http://peterwonka.net/Publications/pdfs/2014.SG.Lipp.PushPull.pdfPushPull++computer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>A1

<01>951GG0http://www.peterwonka.net/Publications/pdfs/2003.SG.Wonka.InstantArchitecture.high.pdfInstant Architecturecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>Z0

<01>SM1GG2http://www.peterwonka.net/Publications/pdfs/2006.SG.Mueller.ProceduralModelingOfBuildings.final.pdfProcedural Modeling of Buildingscomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>g/
<01>%<25>1GG.http://www.proun-game.com/Oogst3D/CODING/InteriorMapping/InteriorMapping.pdfInterior Mapping: A new technique for rendering realistic buildingscomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>O.
<01>
<01>1GG,http://research.microsoft.com/en-us/um/people/cohen/bs.pdfInteractive Horizon Mapping: Shadows for bump-mapped surfacescomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>;-

<01>]1GG+http://www.crytek.com/download/Light_Propagation_Volumes.pdfLight Propagation Volumes in CryEngine 3computer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>,	
w1GG*https://github.com/luanfujun/deep-photo-styletransferCodecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>+	
U?1GG%https://arxiv.org/pdf/1703.07511.pdfDeep Photo Style Transfercomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>b*

<01>3}1GG$http://www.cs.tau.ac.il/~dcor/articles/2013/3-Sweep-Extracting-Editable-Objects.pdf3-Sweep: Extracting Editable Objects from a Single Photocomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>q)
<01><15>71GG&http://research.microsoft.com/pubs/155416/kinectfusion-uist-comp.pdfKinectFusion: Real-time 3D Reconstruction and Interaction Using a Moving Depth Cameracomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>(

<01>1GG*http://www.cs.jhu.edu/~misha/Code/PoissonRecon/Version5.71/Codecomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975<EFBFBD>9'

<01>I1GG#http://research.microsoft.com/en-us/um/people/hoppe/poissonrecon.pdfPoisson surface reconstructioncomputer_graphics/2017-09-11T23:06:15.3833239752017-09-11T23:06:15.383323975

17<0F>3i
V/<0E><0E>{Q
<0A>
i
7<0C><0C>
<01>L<0B><00><0B>j-
<EFBFBD>
<EFBFBD>
g
/	<09>	<09>	q	>	
<08><08>T<07>fg+<06><06>uP
<05>w8<04><04>i<03><03><02>h1X<04>1http://breachattack.com/resources/BREACH%20-%20SSL,%20gone%20in%2030%20seconds.pdf
X<04>1http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.24.9333&rep=rep1&type=pdf<00>
<01>%http://infoscience.epE<04>http:/:whttp://algo.inria.fr/flajolet/Publications/FlMa85.pdf
1http://homepages.inX<04>1http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.13.9460&rep=rep1&type=pdf
._http://en.wikipedia.org/wiki/Suffix_array

http://home.pipeline.com/~hbaker1/NoMotionGC.html<00>W<04>/http://haskell.cs.yale.edu/wp-content/uploads/2012/08/Winograd-Cort-Wormholes.pdf<00>K<04>http://haskell.cs.yale.edu/wp-content/uploads/2011/02/workshop-02.pdf<00>F<04>
http://haskell.cs.yale.edu/wp-cont3ihttp://affect.media.mit.edu/pdfs/95.picard.pdf
/)Uhttp://dreammachin.es/p1-wallace.pdf
+)Uhttp://futuredata.stanford.edu/asap/
\<04>;
http://gatekeeper.dec.com/ftp/pub/dec/SRC/publications/broder/positano-final-wpnums.pdfP<04>!http://gamification-research.org/wp-content/uploads/2011/04/12-Gerling.pdf<00>0e
http://ftp.cs.ucla.edu/pub/stat_ser/r360.pdf
/c
http://ftp.cs.ucla.edu/pub/stat_ser/r30.pdf
8u
http://ftp.cs.ucla.edu/pub/stat_ser/r156-reprint.pdf4m
http://ftp.cs.ucla.edu/pub/stat_ser/R218-B-L.pdf>http://frenchy64.github.io/papers/typed-clojure-draft.pdf<00>X<04>3
http://faculty.salisbury.edu/~xswang/Research/Papers/SERelated/no-silver-bullet.pdfg9uhttp://erlang.org/download/armstrong_thesis_2003.pdf<00>E<04>http://eprints.eemcs.utwente.nl/7281/01/db-utwente-40501F46.pdf<00>$M
http://en.wikipedia.org/wiki/PcrF<04>
http://en.wikipedia.org/wiki/Moving_magnet_and_conductor_problem<00>5o
http://en.wikipedia.org/wiki/HOL_(proof_assistant?8shttp://en.wikipedia.org/wiki/Empirical_algorithmics<00>:whttp://eb.host.cs.st-andrews.ac.uk/drafts/effects.pdf<00>x<04>qhttp://dl.dropboxusercontent.com/u/220532/MindTrek_Gamification_PrinterReady_110806_SDE_accepted_LEN_changes_1.pdf<00>t<04>k
http://diyhpl.us/~bryan/papers2/distributed/distributed-systems/zab.totally-ordered-broadcast-protocol.2008.pdfj<{http://dig.cs.illinois.edu/papers/lambdaRefactoring.pdf<00>*Whttp://ddg.jaist.ac.jp/pub/HDY+04.pdf<00>M<04>http://db.disi.unitn.eu/pages/VLDBProgram/pdf/industry/p871-curtiss.pdf<00>3ihttp://davidsjohnson.net/papers/experguide.pdf<00>2ghttp://cseweb.ucsd.edu/~vahdat/papers/mop.pdf<00>F<04>
http://cs.yale.edu/homes/thomson/publications/calvin-sigmod12.pdfR8u
http://cs.brown.edu/~mph/HerlihyW90/p463-herlihy.pdfo=
http://cs.brown.edu/courses/csci2370/2000/1999/cabral.pdf37qhttp://cs.au.dk/~hosc/local/LaSC-4-3-pp223-242.pdf<00>=
http://cs-www.cs.yale.edu/homes/dna/papers/vll-vldb13.pdfWF<04>
http://cs-www.cs.yale.edu/homes/dna/papers/determinism-vldb10.pdfT@<04>
http://cs-www.cs.yale.edu/homes/dna/papers/abadi-pacelc.pdfU<{http://conal.net/papers/push-pull-frp/push-pull-frp.pdf<00>C<04>http://community.haskell.org/~simonmar/papers/parallel-gc.pdf<00>E<04>http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.148.524<00>W<04>1
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.21.2707&rep=rep1&type=pdfeX<04>3
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.161.6751&rep=rep1&type=pdfXX<04>3
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.108.1302&rep=rep1&type=pdf;8u
http://cidrdb.org/cidr2015/Papers/CIDR15_Paper16.pdfL1ehttp://chaoran.me/assets/pdf/wfq-ppopp16.pdf<00>S<04>+	http://blog.sei.cmu.edu/post.cfm/secure-coding-tools-analyzing-android-apps-118<31><04>%http://bitsavers.informatik.uni-stuttgart.de/pdf/xerox/parc/techReports/CSL-89-1_Epidemic_Algorithms_for_Replicated_Database_Maintenance.pdf<00>)W
http://bayes.cs.ucla.edu/jp_home.html.a
http://barroso.org/publications/isca00.pdf;yhttp://asc.di.fct.unl.pt/~jleitao/pdf/dsn07-leitao.pdf<00>$Khttp://arxiv.org/abs/1507.02988<00>#Ihttp://arxiv.org/abs/1004.4240<00>9uhttp://anil.recoil.org/papers/2013-asplos-mirage.pdf<00>O<04>!
http://airesearch.com/wp-content/uploads/2016/01/deepmind-mastering-go.pdf	F<04>
http://adam.chlipala.net/papers/SqlcachePOPL17/SqlcachePOPL17.pdf
9<00>%
~<03><03>:<00><02><0F>|E<0E>r<
<01>
<0A>
<0A>
v
<
<0C><0C>
F
c)<0B><0B>b[
<EFBFBD>
|
C	<09>	<09>	<09>	_	 <08><08>S6<07><07>h$<06><06>F<05><05>B<04><04>nB<04>http://i<04>U
http://www.cs.duke.edu/courses/cps3_<04>A
http://static.googleuserc@<04>
http://homepages.inf.ed.ac.uk/slindley/papers/handlers.pdf
$5mhttp://okmij.org/ftp/Haskell/extensible/more.pdf
 7qhttp://okmij.org/ftp/Haskell/extensible/exteff.pdf
[<04>7http://haskell.cs.yale.edu/wp-content/uploads/2011/02/POPL96-Modular-interpreters.pdf
N<04>http://lafo.ssw.uni-linz.ac.at/papers/2013_Onward_OneVMToRuleThemAll.pdf
8shttp://ordiecole.com/squeak/cardelli_squeak1985.pdf
>http://papers.ssrn.com/sol3/papers.cfm?abstract_id=208278
a<04>Chttp://homepages.inf.ed.ac.uk/wadler/papers/propositions-as-types/propositions-as-types.pdf<00>6ohttp://home.pipeline.com/~hbaker1/NoMotionGC.html<00>W<04>/http://haskell.cs.yale.edu/wp-content/uploads/2012/08/Winograd-Cort-Wormholes.pdf<00>K<04>http://haskell.cs.yale.edu/wp-content/uploads/2011/02/workshop-02.pdf<00>F<04>
http://haskell.cs.yale.edu/wp-content/uploads/2011/02/rt-frp.pdf<00>H<04>
http://graphics.stanford.edu/papers/stabilization/karpenko_gyro.pdfD<04>
http://research.microsoft.com/pubs/79348/presto27-greenberg.pdffD<04>	http://research.microsoft.com/pubs/255833/IronFleet-twocol.pdf<00>I<04>
http://research.microsoft.com/pubs/155416/kinectfusion-uist-comp.pdf)a<04>Chttp://research.microsoft.com/en-us/um/people/simonpj/papers/history-of-haskell/history.pdf<00>O<04>!
http://research.microsoft.com/en-us/um/people/lamport/pubs/time-clocks.pdf:Q<04>%
http://research.microsoft.com/en-us/um/people/lamport/pubs/lamport-paxos.pdfI<04>
http://research.microsoft.com/en-us/um/people/hoppe/poissonrecon.pdf'S<04>)
http://research.microsoft.com/en-us/um/people/fournet/papers/join-tutorial.pdf~?<04>

http://research.microsoft.com/en-us/um/people/cohen/bs.pdf.C<04>	
http://research.microsoft.com/apps/pubs/default.aspx?id=210931t5o
http://research.google.com/pubs/archive/41684.pdfsU<04>+http://repository.upenn.edu/cgi/viewcontent.cgi?article=1162&context=cis_papers<00>A<04>http://rd.springer.com/content/pdf/10.1007%2FBF00994018.pdf<00>;http://racket-lang.org/<00>Q<04>%
http://publications.lib.chalmers.se/records/fulltext/125252/local_125252.pdf=3ihttp://plosworkshop.org/2013/preprint/kell.pdf<00>F<04>
http://peterwonka.net/Publications/pdfs/2014.SG.Lipp.PushPull.pdf2>http://people.seas.harvard.edu/~chong/pubs/pldi13-elm.pdf<00>2ghttp://people.inf.elte.hu/center/fulltext.pdf<00>8shttp://people.ee.duke.edu/~lcarin/Lihan4.21.06a.pdf<00>3k
http://people.csail.mit.edu/rivest/Rsapaper.pdfDC<04>	
http://people.csail.mit.edu/matei/papers/2013/sosp_sparrow.pdf{8shttp://people.csail.mit.edu/jrb/Projects/dexprs.pdf<00>A<04>
http://people.cs.umass.edu/~emery/pubs/berger-asplos2000.pdfqG<04>
http://pdos.csail.mit.edu/papers/chord:sigcomm01/chord_sigcomm.pdflT<04>)http://pdf.aminer.org/000/465/194/incremental_collection_of_mature_objects.pdf<00>J<04>http://patrickthomson.ghost.io/an-introduction-to-recursion-schemes/<00>X<04>3
http://pages.cs.wisc.edu/~remzi/Classes/739/Spring2004/Papers/optimistic-survey.pdfdc<04>I
http://page.mi.fu-berlin.de/block/htw-lehre/wise2015_2016/bel_und_rend/skripte/gouraud1971.pdf$@<04>
http://orbit.dtu.dk/files/102419168/abstract_ELB_trees.pdf<00>-_
http://notes.stephenholiday.com/Kafka.pdfm2i
http://nms.lcs.mit.edu/papers/ron-sosp2001.pdfy6ohttp://msl.cs.uiuc.edu/~lavalle/papers/Lav98c.pdf<00>9w
http://mcg.cs.tau.ac.il/papers/disc2008-hopscotch.pdfQA<04>
http://maverick.inria.fr/Publications/2009/CNLE09/CNLE09.pdf!6q
http://maverick.inria.fr/Publications/2009/CNLE09/"L<04>http://luthuli.cs.uiuc.edu/~daf/courses/Signals%20AI/Papers/HMMs/0.pdf
5o
http://kowshik.github.io/JPregel/pregel_paper.pdfwG<04>http://jeffreymbradshaw.net/publications/Common_Ground_Single.pdf<00>J<04>http://infoscience.epfl.ch/record/83409/files/neg--1184036295all.pdf<00>?<04>

http://infoscience.epfl.ch/record/169879/files/RMTrees.pdfO6ohttp://ilpubs.stanford.edu:8090/422/1/1999-66.pdf<00>E<04>http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5350749<00>=}http://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf<00>
`m
<0A><0C>P<0B>
<EFBFBD>	<09>	2a<07><06>b<04>`p<02>
<01>
,<00>IK
<01><07>
%GGPhttps://www.cs.unc.edu/~welch/kalman/media/pdf/Kalman1960.pdfA New Approach to Linear Filtering and Prediction Problemsdata_fusion/2017-09-11T23:06:15.4521950682017-09-11T23:06:15.452195068<EFBFBD>6O

<01>
[-GGIhttp://infoscience.epfl.ch/record/169879/files/RMTrees.pdfRRB-Trees: Efficient Immutable Vectorsdata_structures/2017-09-11T23:06:15.4833059082017-09-11T23:06:15.483305908<EFBFBD>aN
<01>
<01>/-GG@http://www.research.ibm.com/people/m/michael/podc-1996.pdfSimple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithmsdata_structures/2017-09-11T23:06:15.4833059082017-09-11T23:06:15.483305908<EFBFBD>$M

<01>3-GGLhttp://www.csd.uoc.gr/~hy460/pdf/Dynamic%20Hash%20Tables.pdfDynamic Hash Tablesdata_structures/2017-09-11T23:06:15.4833059082017-09-11T23:06:15.483305908<EFBFBD>(L	
uK/GGHhttp://cidrdb.org/cidr2015/Papers/CIDR15_Paper16.pdfImmutability Changes Everythingdata_replication/2017-09-11T23:06:15.4544541022017-09-11T23:06:15.454454102<EFBFBD>;J

<01>e'GGGhttp://www.cs.bell-labs.com/who/dmr/pdfs/shannoncryptshrt.pdfA Mathematical Theory of Cryptography (1945)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>I	
U/'GGFhttps://eprint.iacr.org/2016/461.pdfNTRU Prime (2016)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>7H	
ym'GGDhttp://web.cs.ucdavis.edu/~rogaway/papers/moral-fn.pdfThe Moral Character of Cryptographic Work (2015)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>QG
<01><05>'GGChttp://www.cs.tau.ac.il/~tromer/papers/acoustic-20131218.pdfRSA Key Extraction via Low-Bandwidth Acoustic Cryptanalysis (2013)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>-F	
{W'GGEhttp://www-ee.stanford.edu/~hellman/publications/24.pdfNew Directions in Cryptography (1976)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>>E	
{y'GGAhttps://crypto.stanford.edu/~dabo/papers/RSA-survey.pdfTwenty Years of Attacks on the RSA Cryptosystem (1999)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>ND

k<>''GG?http://people.csail.mit.edu/rivest/Rsapaper.pdfA Method for Obtaining Digital Signatures and Public-Key Cryptosystems (1977)cryptography/2017-09-11T23:06:15.4059790042017-09-11T23:06:15.405979004<EFBFBD>JC

<01>'g#GG=https://www.usenix.org/legacy/event/osdi04/tech/full_papers/candea/candea.pdfMicroreboot -- A technique for cheap recoverycrash_only/2017-09-11T23:06:15.4053081052017-09-11T23:06:15.405308105<EFBFBD>2B

<01>+3#GGBhttps://www.usenix.org/legacy/events/hotos03/tech/full_papers/candea/candea.pdfCrash-Only Softwarecrash_only/2017-09-11T23:06:15.4053081052017-09-11T23:06:15.405308105<EFBFBD>aA
<01>	<09>/%GG@http://www.cs.rochester.edu/~scott/papers/1996_PODC_queues.pdfSimple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithmsconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>5@	
{i%GG<https://people.eecs.berkeley.edu/~brewer/cs262/Mesa.pdfExperience with Processes and Monitors in Mesaconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>?	
o%GG;http://en.wikipedia.org/wiki/HOL_(proof_assistantHOLconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>7>	
us%GG9http://www.cl.cam.ac.uk/~pes20/weakmemory/popl09.pdfThe Semantics of x86-CC Multiprocessor Machine Codeconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>Y=
<01>%<25>%GG8http://publications.lib.chalmers.se/records/fulltext/125252/local_125252.pdfFinding Race Conditions in Erlang with QuickCheck and PULSEconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>'<	
i_%GG:http://user.it.uu.se/~kostis/Papers/escape.pdfMessage Analysis for Concurrent Languagesconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918<EFBFBD>f;
<01>3<EFBFBD>%GG7http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.108.1302&rep=rep1&type=pdfHeap Architectures For Concurrent Languages Using Message Passingconcurrency/2017-09-11T23:06:15.4043159182017-09-11T23:06:15.404315918
ef<0E>
<0A>
>~<0B>
D	i<08><07><06>?<04><03>e<02>
<01>
6<00>N`

}<7D>#GG`http://www.erlang.org/download/armstrong_thesis_2003.pdfMaking Reliable Distributed Systems in the Presence of Software Errorsdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>?c

<01>%S#GG]https://amplab.cs.berkeley.edu/wp-content/uploads/2013/03/mdcc-eurosys13.pdfMDCC: Multi-Data Center Consistencydatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>~b
<01>U<EFBFBD>#GG^http://www.cs.duke.edu/courses/cps399.28/current/papers/sigmod07-YangDasdanEtAl-map_reduce_merge.pdfMap-Reduce-Merge: Simplified Relational Data Processing on Large Clustersdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>ba
<01><0F>-#GG[http://zoo.cs.yale.edu/classes/cs422/2013/bib/terry95managing.pdfManaging Update Conflicts in Bayou, a Weakly Connected Replicated Storage Systemdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>,_	
W}#GG\http://www.few.vu.nl/~kgr700/sdd1.pdfIntroduction to a System for Distributed Databases SDD-1datastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>/^	
gs#GGYhttps://cs.uwaterloo.ca/~bernard/hyperdex.pdfHyperDex: A Distributed, Searchable Key-Value Storedatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>L]
<01>	<09>#GGZhttp://www.ics.uci.edu/~yingyib/papers/HaLoop_camera_ready.pdfHaLoop: Efficient Iterative Data Processing on Large Clustersdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>T\

<01>Aa#GGXhttp://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/41344.pdfF1: A Distributed SQL Database That Scalesdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>\[

<01>Aq#GGUhttp://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/36632.pdfDremel: Interactive Analysis of Web-Scale Datasetsdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>[Z

s<>=#GGThttp://www.cs.cmu.edu/~dga/papers/cops-sosp2011.pdfDon’t Settle for Eventual: Scalable Causal Consistency for Wide-Area Storage with COPSdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>DY

g<>#GGShttp://www.ssrc.ucsc.edu/Papers/weil-sc06.pdfCRUSH: Controlled, Scalable, Decentralized Placement of Replicated Datadatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>XX

<01>3w#GGVhttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.161.6751&rep=rep1&type=pdfCassandra - A Decentralized Structured Storage Systemdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD><W	
u#GGRhttp://cs-www.cs.yale.edu/homes/dna/papers/vll-vldb13.pdfLightweight Locking for Main Memory Database Systemsdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>'V	
uU#GGWhttp://sites.computer.org/debull/A13june/calvin1.pdfModularity and Scalability in Calvindatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>NU
<01><03>#GGQhttp://cs-www.cs.yale.edu/homes/dna/papers/abadi-pacelc.pdfConsistency Tradeoffs in Modern Distributed Database System Designdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>=T

<01>e#GGOhttp://cs-www.cs.yale.edu/homes/dna/papers/determinism-vldb10.pdfThe Case for Determinism in Database Systemsdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>-S	
w_#GGMhttp://www-bcf.usc.edu/~wyattllo/papers/f4-osdi14.pdff4: Facebook’s Warm BLOB Storage Systemdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>XR
<01><0F>#GGNhttp://cs.yale.edu/homes/thomson/publications/calvin-sigmod12.pdfCalvin: Fast Distributed Transactions for Partitioned Database Systemsdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>Q	
w/-GGKhttp://mcg.cs.tau.ac.il/papers/disc2008-hopscotch.pdfHopscotch Hashingdata_structures/2017-09-11T23:06:15.4833059082017-09-11T23:06:15.483305908<EFBFBD>P	
w)-GGJhttp://www.it-c.dk/people/pagh/papers/cuckoo-jour.pdfCuckoo Hashingdata_structures/2017-09-11T23:06:15.4833059082017-09-11T23:06:15.483305908

<01>/Dv
<0A><0C><0B>
<01>
Q	<09><08><07><06>(C<00>O/m<02><00>Is

o<>5GGnhttp://research.google.com/pubs/archive/41684.pdfOmega: flexible, scalable schedulers for large compute clustersdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Wq
<01><05>5GGmhttp://people.cs.umass.edu/~emery/pubs/berger-asplos2000.pdfHoard: A Scalable Memory Allocator for Multithreaded Applicationsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<02><00>e5GGhttp://www<77>/i	
}K5GGrhttp://www.eecs.harvard.edu/~waldo/Readings/waldo-94.pdfA Note on Distributed Computingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109G<00>
<01>e5GGphttp://www.cs.utexas.edu/users/lorenzo/corsi/cs380d/papers/paper2-1.pdfPaxos Made Live - An Engineering Perspectivedistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>_t
<01>	<09>5GGohttp://research.microsoft.com/apps/pubs/default.aspx?id=210931Orleans: Distributed Virtual Actors for Programmability and Scalabilitydistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>qr
<01>A<EFBFBD>5GGkhttp://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/41378.pdfMillWheel: Fault-Tolerant Stream Processing at Internet Scaledistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>bp

}<7D>/5GGlhttps://www.cs.cornell.edu/fbs/publications/SMSurvey.pdfImplementing Fault-Tolerant Services Using the State Machine Approach: A Tutorialdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Lo

u<>5GGjhttp://cs.brown.edu/~mph/HerlihyW90/p463-herlihy.pdfLinearizability: A Correctness Condition for Concurrent Objectsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>en

<01>Aq5GGihttp://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/43438.pdfLarge-scale cluster management at Google with Borgdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>9m	
_}5GGghttp://notes.stephenholiday.com/Kafka.pdfKafka: a Distributed Messaging System for Log Processingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>cl
<01><11>5GGhhttp://pdos.csail.mit.edu/papers/chord:sigcomm01/chord_sigcomm.pdfChord: A Scalable Peer-to-peer Lookup Service for Internet Applicationsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Mk

<01>
u5GGfhttp://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.pdfAbove the Clouds: A Berkeley View of Cloud Computingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>sj

<01>kc5GGehttp://diyhpl.us/~bryan/papers2/distributed/distributed-systems/zab.totally-ordered-broadcast-protocol.2008.pdfA simple totally ordered broadcast protocoldistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<00>}K5GGhttp://www.eecs.harvard.edu/~waldo/Readings/waldo-94.pdfA Note on Distributed Computingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>0h

<01>
aGGchttp://scg.unibe.ch/archive/papers/Duca06bTOPLASTraits.pdfTraits: A Mechanism for Fine-Grained Reusedesign/2017-09-11T23:06:15.5506918952017-09-11T23:06:15.550691895<EFBFBD>bg
<01>3<EFBFBD>GGbhttp://faculty.salisbury.edu/~xswang/Research/Papers/SERelated/no-silver-bullet.pdfNo Silver Bullet — Essence and Accidents of Software Engineeringdesign/2017-09-11T23:06:15.5506918952017-09-11T23:06:15.550691895<EFBFBD>cf
<01><0B>3#GGahttp://research.microsoft.com/pubs/79348/presto27-greenberg.pdfTowards a Next Generation Data Center Architecture: Scalability and Commoditizationdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>Ke

<01>1_#GGdhttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.21.2707&rep=rep1&type=pdfThe Dangers of Replication and a Solutiondatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936<EFBFBD>9d

<01>39#GG_http://pages.cs.wisc.edu/~remzi/Classes/739/Spring2004/Papers/optimistic-survey.pdfOptimistic replicationdatastores/2017-09-11T23:06:15.5087839362017-09-11T23:06:15.508783936
.<03><07><07>z<<06>i	<05>I<04><04><0F><0F><03>^f<0E><0E>g
<0A>
<0A>
U
#<0C><0C>^%<0B><0B>]
<EFBFBD>
<EFBFBD>
e
	<09>	o	'<08><03><08>_<02>q,
<01>
<01>
Y
<00>	<00><04>http://www.elizabete.com.br/site/Outros/Entradas/2012/11/19_Revisao_Sistematica_files/ConceitosRevisaoSistematica_Biolchini.pdf
<}
http://www.eecs.harvard.edu/~waldo/Readings/waldo-94.pdfiE<04>

http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.pdfkC<04>http://www.ee.columbia.edu/~dpwe/pubs/BarkCE05-sfd-spcomm.pdf
H<04>http://www.ece.cmu.edu/~ganger/712.fall02/papers/p761-thompson.pdf<00>D<04>
http://www.dna.caltech.edu/courses/cs191/paperscs191/turing.pdfH<04>http://www.diva-portal.org/smash/get/diva2:392243/FULLTEXT01.pdfOn<00>_<04>A
http://www.disneyresearch.com/project/high-quality-single-shot-capture-of-facial-geometry/7d<04>K
http://www.disneyresearch.com/project/coupled-3d-reconstruction-of-sparse-facial-hair-and-skin/6;yhttp://www.csl.mtu.edu/cs646=}http://web.cecs.pdx.edu/~mpj/pubs/composing-fractals.pdf
'>http://www.cs.ox.ac.uk/people/nicolas.wu/papers/Scope.pdf
"I<04>http://www.cs.ru.nl/~W.Swierstra/Publications/DataTypesALaCarte.pdf
!K<04>http://web.media.mit.edu/~minsky/papers/Why%20programming%20is--.html
6ohttp://trec.nist.gov/pubs/trec3/papers/city.ps.gz<00>_<04>A
http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/43438.pdfn_<04>A
http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/41378.pdfr_<04>A
http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/41344.pdf\_<04>A
http://static.googleusercontent.com/media/research.google.com/en/us/pubs/archive/36632.pdf[b<04>G
http://static.googleusercontent.com/media/research.google.com/en/us/archive/chubby-osdi06.pdf}8u
http://sites.computer.org/debull/A13june/calvin1.pdfV6q
http://sigops.org/sosp/sosp13/papers/p33-david.pdf9=
http://sigops.org/sosp/sosp13/papers/p151-mashtizadeh.pdfx3k
http://shapegrammar.org/ifip/SGBestPapers72.pdf4=
http://shapegrammar.org/5?<04>

http://scg.unibe.ch/archive/papers/Duca06bTOPLASTraits.pdfhS<04>'http://researcher.watson.ibm.com/researcher/files/us-bacon/Bacon12AndThen.pdf<00>S<04>)
http://www.cs.rpi.edu/~cutler/classes/advancedgraphics/S08/lectures/kajiya.pdf&C<04>	
http://www.cs.rochester.edu/~scott/papers/1996_PODC_queues.pdfA/ahttp://www.cs.nyu.edu/~mohri/pub/csl01.pdf
G<04>
http://www.cs.northwestern.edu/~ago820/cs395/Papers/Phong_1975.pdf%@<04>
http://www.cs.jhu.edu/~misha/Code/PoissonRecon/Version5.71/(i<04>U
http://www.cs.duke.edu/courses/cps399.28/current/papers/sigmod07-YangDasdanEtAl-map_reduce_merge.pdfbJ<04>
http://www.cs.duke.edu/courses/cps296.4/spring04/papers/Adleman94.pdf=}http://www.cs.cornell.edu/~asdas/research/dsn02-swim.pdf<00>=}http://www.cs.cornell.edu/home/rvr/papers/flowgossip.pdf<00>7s
http://www.cs.cmu.edu/~dga/papers/cops-sosp2011.pdfZC<04>http://www.cs.berkeley.edu/~franklin/Papers/p315-franklin.pdf<00>B<04>
http://www.cs.bell-labs.com/who/dmr/pdfs/shannoncryptshrt.pdfJA<04>
http://www.crytek.com/download/Light_Propagation_Volumes.pdf-B<04>http://www.comp.lancs.ac.uk/~elkhatib//Docs/2014.06_Netw.pdf<00>8u
http://www.cl.cam.ac.uk/~pes20/weakmemory/popl09.pdf>H<04>http://www.cl.cam.ac.uk/research/srg/netos/papers/2003-xensosp.pdf<00>5mhttp://www.ccs.neu.edu/racket/pubs/icfp10-cf.pdf<00>E<04>http://www.cas.mcmaster.ca/~bill/best/algorithms/07Taxonomy.pdf

1g
http://www.bodden.de/pubs/far+14flowdroid.pdfO<04>http://www.berkkapicioglu.com/wp-content/uploads/2013/11/thesis_final.pdf<00>W<04>1
http://www.andrew.cmu.edu/course/15-749/READINGS/required/resilience/lamport82.pdf|i<04>U
http://www.ams.org/journals/tran/1965-117-00/S0002-9947-1965-0170805-7/S0002-9947-1965-0170805-7.pdf;{
http://www-ee.stanford.edu/~hellman/publications/24.pdfF9w
http://www-bcf.usc.edu/~wyattllo/papers/f4-osdi14.pdfS4khttp://winsh.me/papers/erlang_workshop_2013.pdf<00>K<04>http://webcem01.cem.itesm.mx:8005/erlang/cd/downloads/hopl_erlang.pdf<00>:y
http://web.cs.ucdavis.edu/~rogaway/papers/moral-fn.pdfH3ihttp://user.it.uu.se/~kostis/Papers/ismm04.pdf<00>2i
http://user.it.uu.se/~kostis/Papers/escape.pdf<
<00>.<03><0E>.
<01>T<02>
7<0C>
[<0B>
<EFBFBD>
 f	L9<00><00><>:w	
oo5GGshttp://kowshik.github.io/JPregel/pregel_paper.pdfPregel: A System for Large-Scale Graph Processingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109iL<00>#<23>5GGhttps://www.usenix.org/system/files/conference/osdi14/osdi14-<2D>C{

<01>	e5GGvhttp://people.csail.mit.edu/matei/papers/2013/sosp_sparrow.pdfSparrow: Distributed, Low Latency Schedulingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Jx	
5GGuhttp://sigops.org/sosp/sosp13/papers/p151-mashtizadeh.pdfReplication, History, and Grafting in the Ori File Systemdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Mz

q<>5GGthttp://www.mshah.org/papers/sosp_2007_aguilera.pdfSinfonia: A New Paradigm for Building Scalable Distributed Systemsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>Lu

<01>e5GGphttp://www.cs.utexas.edu/users/lorenzo/corsi/cs380d/papers/paper2-1.pdfPaxos Made Live - An Engineering Perspectivedistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<06><00><00><0F>5GGhttp://www.cs.utexas.edu/~shmat/courses/cs395t_fall04/chaum81.pdfUntraceable Electronic Mail, Return Addresses, and Digital Pseudonymsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11<31>a<EFBFBD><02><0F>5GG<00>http://www.cs.utexas.edu/~shmat/courses/cs395t_fall04/chaum81.pdfUntraceable Electronic Mail, Return Addresses, and Digital Pseudonymsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>?<3F>	
us5GG~http://anil.recoil.org/papers/2013-asplos-mirage.pdfUnikernels: Library Operating Systems for the Clouddistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109
<01><00><07>#5GGhttp://www.cs.berkeley.edu/~franklin/Papers/p315-franklin.pdfTransactional Client-Server Cache Consistency: Alternatives and Performancedistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109
<01>	yq5GGhttps://www.cs.cmu.edu/~dga/papers/epaxos-sosp2013.pdfThere Is More Consensus in Egalitarian Parliamentsdistributed_systems/2017-09-11T23:06:15.583<EFBFBD>b<EFBFBD>

<01><07>#5GGhttp://www.cs.berkeley.edu/~franklin/Papers/p315-franklin.pdfTransactional Client-Server Cache Consistency: Alternatives and Performancedistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>P<EFBFBD>

<01>m5GG}http://db.disi.unitn.eu/pages/VLDBProgram/pdf/industry/p871-curtiss.pdfUnicorn: A System for Searching the Social Graphdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>@<40>	
yq5GG|https://www.cs.cmu.edu/~dga/papers/epaxos-sosp2013.pdfThere Is More Consensus in Egalitarian Parliamentsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>=

<01>%=5GG{http://research.microsoft.com/en-us/um/people/lamport/pubs/lamport-paxos.pdfThe Part-Time Parliamentdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>h~
<01>)<29>
5GGzhttp://research.microsoft.com/en-us/um/people/fournet/papers/join-tutorial.pdfThe Join Calculus: a Language for Distributed Mobile Programmingdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>I|

<01>1I5GGyhttp://www.andrew.cmu.edu/course/15-749/READINGS/required/resilience/lamport82.pdfThe Byzantine Generals Problemdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>v}
<01>G<EFBFBD>5GGxhttp://static.googleusercontent.com/media/research.google.com/en/us/archive/chubby-osdi06.pdfThe Chubby Lock Service for Loosely-Coupled Distributed Systemsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD> y	
iA5GGwhttp://nms.lcs.mit.edu/papers/ron-sosp2001.pdfResilient Overlay Networksdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>v
<01>q<EFBFBD>
5GGqhttp://www.itu.dk/stud/speciale/bepjea/xwebtex/litt/practical-byzantine-fault-tolerance-and-proactive-recovery.pdfPractical Byzantine Fault Tolerance and Proactive Recoverydistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109

r)<07>F!<06>a<0B><0C>W<08>r	r<04><03><02> 
8<00>d<EFBFBD><00><07>+3GGhttp://community.haskell.org/~simonmar/papers/parallel-gc.pdfParallel Generational-Copying Garbage Collection with a Block-Structured
  Heapgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>K<EFBFBD>
o<>3GGhttp://home.pipeline.com/~hbaker1/NoMotionGC.htmlThe Treadmill: Real<61>a<EFBFBD><02>!<21>'GG<00>http://gamification-research.org/wp-content/uploads/2011/04/12-Gerling.pdfExploring the Potential of Gamification Among Frail Elderly Personsgamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066<EFBFBD>N<EFBFBD>
<02>{'GG<00>http://www.rolandhubscher.org/courses/hf765/readings/p17-huotari.pdfDefining Gamification - A Service Marketing Perspectivegamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066<EFBFBD>f<EFBFBD>
a<>Q5GG<00>http://www.pmg.csail.mit.edu/papers/vr.pdfViewstamped Replication: A New Primary Copy Method to Support Highly-Available Distributed Systemsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<08><00>#<23>5G<>!<21><02>#<23>5GG<00>https://www.usenix.org/system/files/conference/osdi14/osdi14-paper-yuan.pdfSimple Testing Can Prevent Most Critical Failures:
An Analysis of Production Failures in Distributed
Data-Intensive Systemsdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>%<25>
<02>
#5GG<00>http://en.wikipedia.org/wiki/Moving_magnet_and_conductor_problemasymmetriesdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>P<EFBFBD>	
<02>	}5GG<00>http://research.microsoft.com/pubs/255833/IronFleet-twocol.pdfIronFleet: Proving Practical Distributed Systems Correctdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109<EFBFBD>J<EFBFBD>
<02>
m5GG<00>http://research.microsoft.com/pubs/80693/vl2-sigcomm09-final.pdfVL2: A Scalable and Flexible Data Center Networkdistributed_systems/2017-09-11T23:06:15.5832871092017-09-11T23:06:15.583287109
<EFBFBD>
<00>q<EFBFBD>'<08>P<EFBFBD>
}<7D>'GG<00>http://www.katherineeveritt.com/papers/p457-consolvo.pdfDesign Requirements for Technologies that Encourage Physical Activitygamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066<EFBFBD><0B><02>q<EFBFBD>'GG<00>http://dl.dropboxusercontent.com/u/220532/MindTrek_Gamification_PrinterReady_110806_SDE_accepted_LEN_changes_1.pdfFrom Game Design Elements to Gamefulness: Defining “Gamification”gamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066#

}<7D>'GGhttp://www.katherineeveritt.com/papers/p457-consolvo.pdfDesign Requirements for Technologies that Encourage Physical Activitygamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066#0
<00>{'GGhttp://www.rolandhubscher.org/cour<75><1C>	
s#AGGhttp://en.wikipedia.org/wiki/Empirical_algorithmics(Wikipedia)experimental_algorithmics/2017-09-11T23:06:15.6239860842017-09-11T23:06:15.623986084
<0A><00>
i<>AGGhttp://davidsjohnson.net/papers/experguide.pdfA Theoretician's Guide to the Experimental Analysis of Algorithmsexperimental_algorithmics/2017-0<>O<EFBFBD>
i<>AGG<00>http://davidsjohnson.net/papers/experguide.pdfA Theoretician's Guide to the Experimental Analysis of Algorithmsexperimental_algorithmics/2017-09-11T23:06:15.6239860842017-09-11T23:06:15.623986084<00>
<00>GGGhttp://www.ece.cmu.edu/~ganger/712.fall02/papers/p761-thompson.pdfReflections on Trusting Trustethics/2017-09-11T23:06:15.6229060062017-09-11T23:06:15.622906006<00><00>I<EFBFBD>!GGhttp://www.sci.br<62>,<2C>
<02>GGG<00>http://www.ece.cmu.edu/~ganger/712.fall02/papers/p761-thompson.pdfReflections on Trusting Trustethics/2017-09-11T23:06:15.6229060062017-09-11T23:06:15.622906006<EFBFBD>k<EFBFBD>
<02>I<EFBFBD>!GG<00>http://www.sci.brooklyn.cuny.edu/~parsons/projects/mech-design/publications/bluffers-final.pdfAuctions and bidding: A guide for computer scientists (2011)economics/2017-09-11T23:06:15.6214260252017-09-11T23:06:15.621426025
<08><07>O
j
<0A><0C><0E>(	<09><08><06><05><04><03><02><00><16>"	q=GG<00>http://www.gsd.inesc-id.pt/~ler/reports/srds07.pdfEpidemic Broadcast Treesgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>I<EFBFBD>!
}<7D>GG<00>http://www.cs.cornell.edu/home/rvr/papers/flowgossip.pdfEfficient Reconciliation and Flow Control for Anti-Entropy Protocolsgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD><13> 	y/GG<00>http://www.csl.mtu.edu/cs6461/www/Reading/Birman99.pdfBimodal Multicastgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>3<EFBFBD>	}kGG<00>http://www.soc.napier.ac.uk/~benp/dream/dreampaper17.pdfLarge-Scale Newscast Computing on the Internet gossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>W<EFBFBD>
}<7D>1GG<00>http://www.cs.cornell.edu/~asdas/research/dsn02-swim.pdfSWIM: Scalable Weakly-consistent Infection-style Process Group Membership Protocolgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>q<EFBFBD><02><15>KGG<00>http://infoscience.epfl.ch/record/83409/files/neg--1184036295all.pdfThe Peer Sampling Service: Experimental Evaluation of Unstructured Gossip-Based Implementationsgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD><10>
<02>%{GG<00>http://bitsavers.informatik.uni-stuttgart.de/pdf/xerox/parc/techReports/CSL-89-1_Epidemic_Algorithms_for_Replicated_Database_Maintenance.pdfEpidemic Algorithms for Replicated Database Maintenancegossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>o<EFBFBD><02><0B>E'GG<00>http://www.ic.unicamp.br/~oliveira/doc/Ubicomp2010_MoviPill.pdfMoviPill: Improving Medication Compliance for Elders - Using a Mobile Persuasive Social Gamegamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066<0B><00><>f<EFBFBD><02><07>+3GG<00>http://community.haskell.org/~simonmar/papers/parallel-gc.pdfParallel Generational-Copying Garbage Collection with a Block-Structured
  Heapgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>M<EFBFBD>
o<>3GG<00>http://home.pipeline.com/~hbaker1/NoMotionGC.htmlThe Treadmill: Real-Time Garbage Collection Without Motion Sicknessgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>:<3A>
<02>Y3GG<00>http://www.cs.virginia.edu/~cs415/reading/bacon-garbage.pdfA Unified Theory of Garbage Collectiongarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>Q<EFBFBD>
<02>s3GG<00>http://www.ssw.uni-linz.ac.at/General/Staff/TW/Wuerthinger05Train.pdfIncremental Garbage Collection: The Train Algorithmgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064
<00>)]3GG<47>G<EFBFBD>
y<>GG<00>http://asc.di.fct.unl.pt/~jleitao/pdf/dsn07-leitao.pdfHyParView: a membership protocol for reliable gossip-based broadcastgossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>O<EFBFBD>
<02>)]3GG<00>http://pdf.aminer.org/000/465/194/incremental_collection_of_mature_objects.pdfIncremental Collection of Mature Objectsgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>T<EFBFBD><02>	<09>3GG<00>https://www.cs.purdue.edu/homes/hosking/690M/p611-fenichel.pdfA LISP Garbage-Collector for Virtual-Memory Computer Systemsgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>J<EFBFBD>
q<>3GG<00>https://www.sics.se/~seif/DatalogiII/Book/train.psIncremental Mature Garbage Collection Using the Train Algorithmgarbage_collection/2017-09-11T23:06:15.6538410642017-09-11T23:06:15.653841064<EFBFBD>-<2D>	ke'GG<00>http://www.jennthom.com/papers/gamification.pdfRemoving Gamification from an Enterprise SNSgamification/2017-09-11T23:06:15.6480180662017-09-11T23:06:15.648018066
13<0F>n(<0E><0E>G
<0A>
<0A>
q
/
<0C><0C>M<0B>y
<EFBFBD>
k
&	<09>	<09>	S	<08>R(<07><07>l(<06><06>0<05><05>h%<04>e<04>k'3<03>b2<02>1ehttp://www.people.hbs.edu/jlerner/simple.pdf
2m<04>[http://www.mit.edu/~dbertsim/papers/Revenue%20Management/Optimal%20Bidding%20in%20Online%20Auctions.pdf
1^<04>=http://www.pps.univ-paris-diderot.fr/~saurin/Enseignement/LMFI/articles/Martin-Lof83.pdf<00>/ahttp://www.pmg.csail.mit.edu/papers/vr.pdf<00>h<04>S
http://www.peterwonka.net/Publications/pdfs/2006.SG.Mueller.ProceduralModelingOfBuildings.final.pdf0[<04>9
http://www.peterwonka.net/Publications/pdfs/2003.SG.Wonka.InstantArchitecture.high.pdf1C<04>http://www.msr-waypoint.net/en-us/groups/ese/nagappan_tdd.pdf
5mhttp://www.msr-waypoint.com/pubs/64346/dwork.pdf<00>6q
http://www.mshah.org/papers/sosp_2007_aguilera.pdfzL<04>http://www.lix.polytechnique.fr/~rousseau/papers/rousseau-cikm2013.pdf<00>B<04>http://www.kdd.org/kdd2016/papers/files/rfp0573-ribeiroA.pdf<00>T<04>)http://www.kavrakilab.org/sites/default/files/kavraki1996prm-high-dim-conf.pdf<00>=}http://www.katherineeveritt.com/papers/p457-consolvo.pdf<00>4khttp://www.jennthom.com/papers/gamification.pdf<00>w<04>q
http://www.itu.dk/stud/speciale/bepjea/xwebtex/litt/practical-byzantine-fault-tolerance-and-proactive-recovery.pdfv9w
http://www.it-c.dk/people/pagh/papers/cuckoo-jour.pdfPE<04>http://www.inf.ed.ac.uk/teaching/courses/exc/reading/morris.pdf
C<04>	
http://www.ics.uci.edu/~yingyib/papers/HaLoop_camera_ready.pdf]=}http://www.icg.tugraz.at/Members/steinber/scatteralloc-1<00>E<04>http://www.ic.unicamp.br/~oliveira/doc/Ubicomp2010_MoviPill.pdf<00>7qhttp://www.gsd.inesc-id.pt/~ler/reports/srds07.pdf<00>)W
http://www.few.vu.nl/~kgr700/sdd1.pdf_<}
http://www.erlang.org/download/armstrong_thesis_2003.pdf`<60><04>http://www.elizabete.com.br/site/Outros/Entradas/2012/11/19_Revisao_Sistematica_files/ConceitosRevisaoSistematica_Biolchini.pdf
<}
http://www.eecs.harvard.edu/~waldo/Readings/waldo-94.pdfiE<04>

http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.pdfkC<04>http://www.ee.columbia.edu/~dpwe/pubs/BarkCE05-sfd-spcomm.pdf
H<04>http://www.ece.cmu.edu/~ganger/712.fall02/papers/p761-thompson.pdf<00>D<04>
http://www.dna.caltech.edu/courses/cs191/paperscs191/turing.pdfH<04>http://www.diva-portal.org/smash/get/diva2:392243/FULLTEXT01.pdfOn<00>_<04>A
http://www.disneyresearch.com/project/high-quality-single-shot-capture-of-facial-geometry/7d<04>K
http://www.disneyresearch.com/project/coupled-3d-reconstruction-of-sparse-facial-hair-and-skin/6;yhttp://www.csl.mtu.edu/cs6461/www/Reading/Birman99.pdf<00>\<04>9http://www.csee.umbc.edu/courses/undergraduate/CMSC331/resources/papers/sammet1972.pdf<00>:y
http://www.csee.umbc.edu/courses/471/papers/turing.pdf8u
http://www.cse.psu.edu/~duo114/pubs/octeau-sec13.pdfA<04>
http://www.csd.uoc.gr/~hy460/pdf/Dynamic%20Hash%20Tables.pdfM:whttp://www.cs.yale.edu/homes/zwan/papers/mcu/efrp.pdf<00>+Yhttp://www.cs.washington.edu/node/4749<00>A<04>http://www.cs.virginia.edu/~cs415/reading/bacon-garbage.pdf<00>@<04>
http://www.cs.uvm.edu/~icdm/algorithms/10Algorithms-08.pdf<00>G<04>http://www.cs.utexas.edu/~shmat/courses/cs395t_fall04/chaum81.pdf<00>L<04>
http://www.cs.utexas.edu/users/lorenzo/corsi/cs380d/papers/paper2-1.pdfuW<04>/http://www.cs.ucsb.edu/~veronika/MAE/spacecomplexityapproxfreqmoments_alon_99.pdf
	A<04>http://www.cs.ucf.edu/courses/cop4020/sum2009/CSP-hoare.pdf<00>F<04>
http://www.cs.tufts.edu/~nr/cs257/archive/luc-maranget/jun08.pdf<00>E<04>http://www.cs.tufts.edu/~nr/cs257/archive/john-hughes/quick.pdf<00>O<04>http://www.cs.tufts.edu/~nr/cs257/archive/chris-okasaki/breadth-first.pdf<00>A<04>
http://www.cs.tau.ac.il/~tromer/papers/acoustic-20131218.pdfG
<03>
&D<0E>
<0A>
)<0C><0B>)
\	<09>	5<06><05>
&
<01><02>=<00>P<EFBFBD>1

u<>/GG`http://erlang.org/download/armstrong_thesis_2003.pdfMaking reliable distributed systems in the presence of software errorslanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.703535889<EFBFBD>/<2F>2
<02>3/GG<00>http://webcem01.cem.itesm.mx:8005/erlang/cd/downloads/hopl_erlang.pdfA History of Erlanglanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.703535889<EFBFBD>]<5D>3<02><11>/GG<00>http://www.diva-portal.org/smash/get/diva2:392243/FULLTEXT01.pdfOnCharacterizing the Scalability of Erlang VM on Many-core Processorslanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.703535889<04><00>	kg/GGhttp://winsh.me/papers/erlang_workshop_2013.pdfOn the Scalability of the Erlang Term Storagelanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.7035<EFBFBD>2<EFBFBD>4	kg/GG<00>http://winsh.me/papers/erlang_workshop_2013.pdfOn the Scalability of the Erlang Term Storagelanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.703535889<00>
u<>/GGhttp://erlang.org/download/armstrong_thesis_2003.pdfMaking reliable distributed systems in the presence of software errorslanguages/erlang/2017-09-11T23:06:15.7035358892017-09-11T23:06:15.703535889<EFBFBD>><3E>0	KyUGG<00>http://arxiv.org/abs/1507.02988Programmatic and Direct Manipulation, Together at Lastlanguages/domain-specific-languages/2017-09-11T23:06:15.7029560552017-09-11T23:06:15.702956055<EFBFBD>)<29>/	gW1GG<00>http://people.inf.elte.hu/center/fulltext.pdfQuickCheck Testing for Fun and Profitlanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD>]<5D>.<02><0B>1GG<00>http://www.cs.tufts.edu/~nr/cs257/archive/john-hughes/quick.pdfQuickCheck: A Lightweight Tool for Random Testing of Haskell Programslanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD>l<EFBFBD>-<02><1F>!1GG<00>http://www.cs.tufts.edu/~nr/cs257/archive/chris-okasaki/breadth-first.pdfBreadth-First Numbering: Lessons from a Small Exercise in Algorithm Designlanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD><1A>,	g91GG<00>https://www.lri.fr/~filliatr/publis/enum2.pdfBacktracking Iteratorslanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD>4<EFBFBD>+	U1GG<00>http://frenchy64.github.io/papers/typed-clojure-draft.pdfPractical Optional Types for Clojurelanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD>I<EFBFBD>*
<02>
o1GG<00>http://www.cs.tufts.edu/~nr/cs257/archive/luc-maranget/jun08.pdfCompiling Pattern Matching to good Decision Treeslanguages/clojure/2017-09-11T23:06:15.6991608892017-09-11T23:06:15.699160889<EFBFBD><1C>)	m53GG<00>http://www.msr-waypoint.com/pubs/64346/dwork.pdfDifferential Privacyinformation_theory/2017-09-11T23:06:15.6969179692017-09-11T23:06:15.696917969<EFBFBD>><3E>(	oq9GG<00>https://www.cs.cornell.edu/home/kleinber/auth.pdfAuthoritative Sources in a Hyperlinked Environmentinformation_retrieval/2017-09-11T23:06:15.6729851072017-09-11T23:06:15.672985107<EFBFBD><1A>'	o)9GG<00>http://trec.nist.gov/pubs/trec3/papers/city.ps.gzOkapi at TREC3information_retrieval/2017-09-11T23:06:15.6729851072017-09-11T23:06:15.672985107<EFBFBD>D<EFBFBD>&	o}9GG<00>http://ilpubs.stanford.edu:8090/422/1/1999-66.pdfThe PageRank Citation Ranking: Bringing Order to the Webinformation_retrieval/2017-09-11T23:06:15.6729851072017-09-11T23:06:15.672985107<EFBFBD>:<3A>%
<02>=9GG<00>http://www.lix.polytechnique.fr/~rousseau/papers/rousseau-cikm2013.pdfGraph of Word and TW-IDFinformation_retrieval/2017-09-11T23:06:15.6729851072017-09-11T23:06:15.672985107<EFBFBD><11>$	WMGG<00>http://ddg.jaist.ac.jp/pub/HDY+04.pdfThe ϕ Accrual Failure Detector gossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066<EFBFBD>8<EFBFBD>#
<02>]GG<00>https://ecommons.cornell.edu/bitstream/handle/1813/7341/98-1687.pdfA Gossip-Style Failure Detection Servicegossip/2017-09-11T23:06:15.6716430662017-09-11T23:06:15.671643066

Y
(
 5r
<EFBFBD>	<09><08>?<07><06>5w
Y<04><03><00>/<2F>Q	ia1GG<00>http://plosworkshop.org/2013/preprint/kell.pdfThe operating system: should there be one?operating_systems/2017-09-11T23:06:15.8643869632017-09-11T23:06:15.864386963<EFBFBD>p<EFBFBD>U<02><1F>)1GG<00>https://us-east.manta.joyent.com/bcantrill/public/ppwl-cantrill-zones.pdfSolaris Zones: Operating System Support for Consolidating Commercial Workloadsoperating_systems/2017-09-11T23:06:15.8643869632017-09-11T23:06:15.864386963<EFBFBD>F<EFBFBD>T
<02>W1GG<00>https://us-east.manta.joyent.com/bcantrill/public/ppwl-cantrill-jails.pdfJails: Confining the omnipotent root.operating_systems/2017-09-11T23:06:15.8643869632017-09-11T23:06:15.864386963<EFBFBD>;<3B>S
<02>O1GG<00>http://www.cl.cam.ac.uk/research/srg/netos/papers/2003-xensosp.pdfXen and the Art of Virtualizationoperating_systems/2017-09-11T23:06:15.8643869632017-09-11T23:06:15.864386963<EFBFBD>j<EFBFBD>R<02><05>71GG<00>https://people.csail.mit.edu/nickolai/papers/clements-sc.pdfThe Scalable Commutativity Rule: Designing Scalable Software for Multicore Processorsoperating_systems/2017-09-11T23:06:15.8643869632017-09-11T23:06:15.864386963<EFBFBD>:<3A>P
<02>
Q=GG<00>http://orbit.dtu.dk/files/102419168/abstract_ELB_trees.pdfEfficient Lock-free B+trees (2014)non_blocking_algorithms/2017-09-11T23:06:15.8364030762017-09-11T23:06:15.836403076<EFBFBD>:<3A>O	eo=GG<00>http://chaoran.me/assets/pdf/wfq-ppopp16.pdfA Wait-free Queue as Fast as Fetch-and-Add (2016)non_blocking_algorithms/2017-09-11T23:06:15.8364030762017-09-11T23:06:15.836403076<EFBFBD><15>N	M==GG<00>https://arxiv.org/abs/1510.00116A Wait-Free Stack (2015)non_blocking_algorithms/2017-09-11T23:06:15.8364030762017-09-11T23:06:15.836403076<EFBFBD>/<2F>M
<02>UGG<00>http://www.comp.lancs.ac.uk/~elkhatib//Docs/2014.06_Netw.pdfCan SPDY Really Make the Web Faster?networks/2017-09-11T23:06:15.8355119632017-09-11T23:06:15.835511963<EFBFBD>%<25>L	qWGG<00>http://www.reed.com/dpr/locus/Papers/EndtoEnd.htmlEnd-to-End Arguments in System Designnetworks/2017-09-11T23:06:15.8355119632017-09-11T23:06:15.835511963<EFBFBD>c<EFBFBD>K
{<7B>51GG<00>http://www.rdrop.com/users/paulmck/RCU/hart_ipdps06.pdfMaking Lockless Synchronization Fast: Performance Implications of Memory Reclamationmemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>V<EFBFBD>J
}<7D>1GG<00>http://www.icg.tugraz.at/Members/steinber/scatteralloc-1ScatterAlloc: Massively Parallel Dynamic Memory Allocation for the GPUmemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>E<EFBFBD>I
<02>C11GG<00>https://www.usenix.org/legacy/publications/library/proceedings/bos94/full_papers/bonwick.psPOSTSCRIPT versionmemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>?<3F>H
<02>A'1GG<00>https://www.usenix.org/legacy/publications/library/proceedings/bos94/full_papers/bonwick.aASCII versionmemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>g<EFBFBD>G<02>/<2F>1GG<00>https://www.usenix.org/legacy/publications/library/proceedings/bos94/bonwick.htmlThe Slab Allocator: An Object-Caching Kernel Memory Allocatormemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD><04>F<02>'<27>I1GG<00>http://researcher.watson.ibm.com/researcher/files/us-bacon/Bacon12AndThen.pdfAnd Then There Were None: A Stall-Free Real-Time Garbage Collector for Reconfigurable Hardwarememory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>^<5E>E
i<>=1GG<00>http://user.it.uu.se/~kostis/Papers/ismm04.pdfMessage Analysis Guided Allocation and Low Pause Incremental GC in a Concurrent Languagememory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018<EFBFBD>r<EFBFBD>D<02>+<2B>!1GG<00>https://cs.brown.edu/~sk/Publications/Papers/Published/cgkmf-teach-gc/paper.pdfTeaching Garbage Collection without Implementing Compilers or Interpretersmemory_management/2017-09-11T23:06:15.8240930182017-09-11T23:06:15.824093018

3
/<0B><0B><0B>e8
<EFBFBD>
<EFBFBD>
_
-	<09>
<01>	<09>	<09>2
<01>
me	><0C><08><08><07><08>
<06><02><06>?
<05>C<05>
/W<0C>1-<04><04>s><03>D<02>r<0F>%<0E>'
<0A>.msr-waypoint.C<04>http://www.msr-waypoint.net/en-us/groups/ese/nagappan_tdd.pdf

bhttp://www.gsd.inesc-id.pt/~ler/reports/srds07.pdf<00>)W
http://www.few.vu.nl/~kgr700/sdd1.pdf_O<04>https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm

ht>http://www.voelter.de/data/pub/projectingModuleFuture.pdf
J<04>http://www.techzoom.net/Papers/Browser_Silent_Updates_%282009%29.pdf
*"http://www.kavrakilab.org/sit2ghttp://www.vmware.com/pdf/asplos235_adams.pdf
5mhttp://www.roboticsproceedings.org/rss01/p36.pdf<00>/ahttps://arxiv.org/pdf/quant-ph/9605043.pdf<00>x<04>qhttps://github.com/papers-we-love/papers-we-love/blob/master/plt/fundamental-concepts-in-programming-languages.pdf<00>f<04>Mhttps://github.com/papers-we-love/papers-we-love/blob/master/mathematics/transcendence-of-pi.pdfÁ<04>%
https://github.com/papers-we-love/papers-we-love/blob/master/caching/a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdf<16><04>
https://github.com/papers-we-love/papers-we-love/blob/master/artificial_intelligence/3-bayesian-network-inference-algorithm.pdf9w
https://github.com/luanfujun/deep-photo-styletransfer,.a
https://github.com/ibab/tensorflow-wavenet)W
https://github.com/basveeling/wavenet(U
https://eprint.iacr.org/2016/461.pdfII<04>https://ecommons.cornell.edu/bitstream/handle/1813/7341/98-1687.pdf<00>B<04>
https://deepmind.com/blog/wavenet-generative-model-raw-audio/1g
https://cs.uwaterloo.ca/~bernard/hyperdex.pdf^U<04>+https://cs.brown.edu/~sk/Publications/Papers/Published/cgkmf-teach-gc/paper.pdf<00>;{
https://crypto.stanford.edu/~dabo/papers/RSA-survey.pdfE/ahttps://arxiv.org/pdf/quant-ph/9508027.pdf<00>(U
https://arxiv.org/pdf/1703.07511.pdf+8
ht@<04>
https://github.com/adamstark/Chord-Detector-and-Chromagram
&<04>https://github.com/papers-we-love/papers-we-love/blob/master/plt/on-understanding-types-data-abstraction-polymorphism.pdf<00>%Mhttps://arxiv.org/abs/1512.02900<00>L<04>http://www.thocp.net/biographies/papers/backus_turingaward_lecture.pdf<00>7qhttp://xlinux.nist.gov/dads//HTML/ahoCorasick.html<00>(U
https://arxiv.org/pdf/1609.03499.pdf%Mhttps://arxiv.org/abs/1510.00116<00>Q<04>%
https://amplab.cs.berkeley.edu/wp-content/uploads/2013/03/mdcc-eurosys13.pdfcF<04>
http://zoo.cs.yale.edu/classes/cs422/2013/bib/terry95managing.pdfa*Y
http://www.vldb.org/conf/1994/P439.PDF0e
http://www.turingarchive.org/browse.php/B/12K<04>http://www.ssw.uni-linz.ac.at/General/Staff/TW/Wuerthinger05Train.pdf<00>1g
http://www.ssrc.ucsc.edu/Papers/weil-sc06.pdfY=}http://www.soc.napier.ac.uk/~benp/dream/dreampaper17.pdf<00>5o
http://www.sci.utah.edu/~bsumma/projects/weaving/8d<04>Ihttp://www.sci.brooklyn.cuny.edu/~parsons/projects/mech-design/publications/bluffers-final.pdf<00>J<04>http://www.rolandhubscher.org/courses/hf765/readings/p17-huotari.pdf<00>?<04>

http://www.research.ibm.com/people/m/michael/podc-1996.pdfN7qhttp://www.reed.com/dpr/locus/Papers/EndtoEnd.html<00><{http://www.rdrop.com/users/paulmck/RCU/hart_ipdps06.pdf<00>
http://ahttps://dl.acm.org/citation.cfm?id=2486019
3'Qhttps://github.com/marsyas/marsyas
)$Khttps://github.com/MTG/essentia
(<28>+<04>Whttps://ac.els-cdn.com/0890540191900524/1-s2.0-0890540191900524-main.pdf?_tid=45497e1c-b5c9-11e7-963f-00000aacb361&acdnat=1508526351_2f3bf288ce0f81ff89fb10ece92eeb9e
O<04>http://www3.alcatel-lucent.com/bstj/vol34-1955/articles/bstj34-5-1045.pdf
i<04>Shttps://github.com/papers-we-love/papers-we-love/blob/master/plt/theory-in-programming-practice.pdf<00>}<04>{https://github.com/papers-we-love/papers-we-love/blob/master/plt/the-derivative-of-a-regular-type-one-hole-contexts.pdf<00><04>https://github.com/papers-we-love/papers-we-love/blob/master/plt/programming-languages-application-and-interpretation.pdf<00>y<04>shttps://github.com/papers-we-love/papers-we-love/blob/master/plt/principal-type-schemes-for-functional-programs.pdf<00>`<04>Ahttps://github.com/papers-we-love/papers-we-love/blob/master/plt/predicate-dispatching.pdf<00>

!01
r0<03>eH
<0A>
	A<08>+/<02>
<01>
!
!<21>m<EFBFBD>X<02><0B>OGG<00>http://eprints.eemcs.utwente.nl/7281/01/db-utwente-40501F46.pdfFunctional Programming with Bananas, Lenses, Envelopes and Barbed Wireparadigms/functional_programming/2017-09-11T23:06:15.8949589842017-09-11T23:06:15.894958984<04>Q
<00>C7GGhttp://homepages.inf.ed.ac.uk/wadler/papers/propositions-as-types/p<>;<3B>W	qSOGG<00>http://cs.au.dk/~hosc/local/LaSC-4-3-pp223-242.pdfOrganizing Programs Without Classesparadigms/functional_programming/2017-09-11T23:06:15.8949589842017-09-11T23:06:15.894958984<EFBFBD>Q<EFBFBD>V
<02>mAGG<00>http://jeffreymbradshaw.net/publications/Common_Ground_Single.pdfCommon Ground and Coordination in Joint Activityorganizational_simulation/2017-09-11T23:06:15.8778430182017-09-11T23:06:15.877843018<EFBFBD>l<EFBFBD>Z
{<7B>)OGG<00>http://dig.cs.illinois.edu/papers/lambdaRefactoring.pdfCrossing the Gap from Imperative to Functional Programming through Refactoringparadigms/functional_programming/2017-09-11T23:06:15.8949589842017-09-11T23:06:15.894958984<EFBFBD>O<EFBFBD>Y
<02>UOGG<00>http://patrickthomson.ghost.io/an-introduction-to-recursion-schemes/An introduction to Recursion Schemesparadigms/functional_programming/2017-09-11T23:06:15.8949589842017-09-11T23:06:15.894958984f<00><19>[GGhttp://www.thocp.net/biographies/papers/backus_turingaward_lecture.pdfCan Programming Be Liberated from the von Neumann Style? A Functional Style and Its Algebra of Programsplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912h	q5/GGhttp://xlinux.nist.gov/dads//HTML/ahoCorasick.htmlAho–Corasick entrypattern_matching/2017-09-11T23:06:15.9460258792017-09-11T23:06:15.946025879j;/GGhttp://racket-lang.org/Racketpattern_matching/2017-09-11T23:06:15.9460258792017-09-11T23:06:15.946025879l
g<>
YGGhttp://cseweb.ucsd.edu/~vahdat/papers/mop.pdfMetaobject protocols: Why we wa<77>x<EFBFBD>e<02><19>[GG<00>http://www.thocp.net/biographies/papers/backus_turingaward_lecture.pdfCan Programming Be Liberated from the von Neumann Style? A Functional Style and Its Algebra of Programsplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD><1C>d	q5/GG<00>http://xlinux.nist.gov/dads//HTML/ahoCorasick.htmlAho–Corasick entrypattern_matching/2017-09-11T23:06:15.9460258792017-09-11T23:06:15.946025879s<EFBFBD>c	;/GG<00>http://racket-lang.org/Racketpattern_matching/2017-09-11T23:06:15.9460258792017-09-11T23:06:15.946025879<EFBFBD>Y<EFBFBD>b
g<>
YGG<00>http://cseweb.ucsd.edu/~vahdat/papers/mop.pdfMetaobject protocols: Why we want them and what else they can doparadigms/object_oriented_programming/2017-09-11T23:06:15.9451201172017-09-11T23:06:15.945120117<EFBFBD>d<EFBFBD>a
<02>'[aGG<00>https://www.seas.harvard.edu/sites/default/files/files/archived/Czaplicki.pdfElm: Concurrent FRP for Functional GUIsparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>O<EFBFBD>_	{_aGG<00>http://conal.net/papers/push-pull-frp/push-pull-frp.pdfPush-Pull Functional Reactive Programmingparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>f<EFBFBD>`
<02>/WaGG<00>http://haskell.cs.yale.edu/wp-content/uploads/2012/08/Winograd-Cort-Wormholes.pdfWormholes: Introducing Effects to FRPparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>]<5D>^	waGG<00>http://people.seas.harvard.edu/~chong/pubs/pldi13-elm.pdfAsynchronous Functional Reactive Programming for GUIsparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>=<3D>]
<02>
'aGG<00>http://haskell.cs.yale.edu/wp-content/uploads/2011/02/rt-frp.pdfReal-Time FRPparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>_<EFBFBD>[
<02>aaGG<00>http://haskell.cs.yale.edu/wp-content/uploads/2011/02/workshop-02.pdfFunctional Reactive Programming, Continuedparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992<EFBFBD>4<EFBFBD>\	w-aGG<00>http://www.cs.yale.edu/homes/zwan/papers/mcu/efrp.pdfEvent-Driven FRPparadigms/functional_reactive_programming/2017-09-11T23:06:15.9127919922017-09-11T23:06:15.912791992
X
23<05><03>
2<02>
$(!
R<06><08>n<02>
<01><00><00>l<EFBFBD>|<00>)<29>-GGhttp://www.kavrakilab.org/sites/default/files/kavraki1996pr<70>i<EFBFBD>k
<02>qgGG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/fundamental-concepts-in-programming-languages.pdfFundamental Concepts in Programming Languagesplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>C<EFBFBD>f
w<>GG<00>http://eb.host.cs.st-andrews.ac.uk/drafts/effects.pdfProgramming and Reasoning with Algebraic Effects and Dependent Typesplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>9<EFBFBD>m
<02>A7GG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/predicate-dispatching.pdfPredicate Dispatchingplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>1<EFBFBD>i	wsGG<00>https://www.cs.utah.edu/plt/publications/macromod.pdfComposable and Compilable Macros: You Want it When?plt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912p<00>
<00>C7GGhttp://homepages.inf.ed.ac.uk/wadler/papers/propositions-as-types/propositions-as-types.pdfPropositions as Typesplt/2017-09-11T23:06:15.9704099122017-09-11T23:06<30>:<3A>j
<02>C7GG<00>http://homepages.inf.ed.ac.uk/wadler/papers/propositions-as-types/propositions-as-types.pdfPropositions as Typesplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>'<27>h
<02>1#GG<00>http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.24.9333&rep=rep1&type=pdfSoft Typingplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912
<00>9_GGhttp<74>-<2D>r
<02>Q!GG<00>http://www.cs.ucf.edu/courses/cop4020/sum2009/CSP-hoare.pdfCommunicating Sequential Processesprocesses/2017-09-11T23:06:15.9906779792017-09-11T23:06:15.990677979<EFBFBD>I<EFBFBD>g
<02>9_GG<00>http://www.csee.umbc.edu/courses/undergraduate/CMSC331/resources/papers/sammet1972.pdfProgramming Languages: History and Futureplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912	<09><00>
<00>O!GGhttps://moodle.risc.jku.at/pluginfile.php/3407/mod_resource/content/1/A%20Calculus%20of%20Communicating%20Systems%5B1980%5D.pdfCalculus of Communicating System<65>p<EFBFBD>s
<02>O!GG<00>https://moodle.risc.jku.at/pluginfile.php/3407/mod_resource/content/1/A%20Calculus%20of%20Communicating%20Systems%5B1980%5D.pdfCalculus of Communicating Systemsprocesses/2017-09-11T23:06:15.9906779792017-09-11T23:06:15.990677979<00>
<00>SIGGhttps://github.com/papers-we-love/papers-we-love/blob/master/plt/theory-in-programming-practice.pdfTheory in Programming Practiceplt/2017-09-11T23:06:15.9704099122<EFBFBD>K<EFBFBD>q
<02>SIGG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/theory-in-programming-practice.pdfTheory in Programming Practiceplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD><03>p<02>{<7B>GG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/the-derivative-of-a-regular-type-one-hole-contexts.pdfThe Derivative of a Regular Type is its Type of One-Hole Contextsplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>x<EFBFBD>o
<02>wGG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/programming-languages-application-and-interpretation.pdfProgramming Languages: Application and Interpretationplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>k<EFBFBD>n
<02>siGG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/principal-type-schemes-for-functional-programs.pdfPrincipal type-schemes for functional programsplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<EFBFBD>~<7E>l<02><EFBFBD>
GG<00>https://github.com/papers-we-love/papers-we-love/blob/master/plt/on-understanding-types-data-abstraction-polymorphism.pdfOn Understanding Types,
Data Abstraction, and Polymorphismplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912<00>
<00>qgGGhttps://github.com/papers-we-love/papers-we-love/blob/master/plt/fundamental-concepts-in-programming-languages.pdfFundamental Concepts in Programming Languagesplt/2017-09-11T23:06:15.9704099122017-09-11T23:06:15.970409912
`@S
<0A><0C>
@
<EFBFBD>	<09><08>3cw<04>%h<02>
<01>`<00>,<2C><02>3<EFBFBD>7GG
https://github.com/papers-we-love/papers-we-love/blob/master/sublinear_algorithms/An-Elementary-Proof-of-a-Theorem-of-Johnson-and-Lindenstrauss.pdfAn Elementary Proof of a Theorem of Johnson and Lindenstrausssublinear_algorithms/2017-09-11T23:06:16.0939550782017-09-11T23:06:16.093955078<EFBFBD><10><02>
<01>
7GG
https://github.com/papers-we-love/papers-we-love/blob/master/sublinear_algorithms/1985-Flajolet-Probabilistic-counting.pdfProbablistic Counting Algorithms for Database Applicationssublinear_algorithms/2017-09-11T23:06:16.0939550782017-09-11T23:06:16.093955078<EFBFBD>@<40>
<02>W%GG
https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithmBoyer–Moore string search algorithmstringology/2017-09-11T23:06:16.0714951172017-09-11T23:06:16.071495117<EFBFBD>9<EFBFBD>
<02>17%GG
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.13.9460&rep=rep1&type=pdfFast String Searchingstringology/2017-09-11T23:06:16.0714951172017-09-11T23:06:16.071495117<EFBFBD><07>	_'%GG<00>http://en.wikipedia.org/wiki/Suffix_arraysuffix arraysstringology/2017-09-11T23:06:16.0714951172017-09-11T23:06:16.071495117<EFBFBD>C<EFBFBD>

<02>q%GG

http://www.cas.mcmaster.ca/~bill/best/algorithms/07Taxonomy.pdfA Taxonomy of Suffix Array Construction Algorithmsstringology/2017-09-11T23:06:16.0714951172017-09-11T23:06:16.071495117<EFBFBD>h<EFBFBD>	<02>/<2F>7GG
http://www.cs.ucsb.edu/~veronika/MAE/spacecomplexityapproxfreqmoments_alon_99.pdfThe Space Complexity of Approximating the Frequency Momentsstreaming_algorithms/2017-09-11T23:06:16.0709570312017-09-11T23:06:16.070957031<EFBFBD>L<EFBFBD>
w<>7GG
http://algo.inria.fr/flajolet/Publications/FlMa85.pdfProbabilistic Counting Algorithms for Data Base Applicationsstreaming_algorithms/2017-09-11T23:06:16.0709570312017-09-11T23:06:16.070957031<EFBFBD>M<EFBFBD>
<02>s7GG
http://www.inf.ed.ac.uk/teaching/courses/exc/reading/morris.pdfCounting large numbers of events in small registersstreaming_algorithms/2017-09-11T23:06:16.0709570312017-09-11T23:06:16.070957031<EFBFBD>F<EFBFBD>
<02>m3GG<00>http://www.ee.columbia.edu/~dpwe/pubs/BarkCE05-sfd-spcomm.pdfDecoding speech in the presence of other sourcesspeech_recognition/2017-09-11T23:06:16.0620839842017-09-11T23:06:16.062083984<EFBFBD>9<EFBFBD>	a{3GG<00>http://www.cs.nyu.edu/~mohri/pub/csl01.pdfWeighted Finite-State Transducers in Speech Recognitionspeech_recognition/2017-09-11T23:06:16.0620839842017-09-11T23:06:16.062083984<EFBFBD>r<EFBFBD><02><19>13GG<00>http://luthuli.cs.uiuc.edu/~daf/courses/Signals%20AI/Papers/HMMs/0.pdfA tutorial on hidden Markov models and selected applications in speech recognitionspeech_recognition/2017-09-11T23:06:16.0620839842017-09-11T23:06:16.062083984<EFBFBD>;<3B>
<02>]GG<00>http://www.techzoom.net/Papers/Browser_Silent_Updates_%282009%29.pdfWhy Silent Updates Boost Security (2009)security/2017-09-11T23:06:16.0456398932017-09-11T23:06:16.045639893<EFBFBD>I<EFBFBD>
<02>1]GG<00>http://breachattack.com/resources/BREACH%20-%20SSL,%20gone%20in%2030%20seconds.pdfBreach: Reviving The Crime Attack (2013)security/2017-09-11T23:06:16.0456398932017-09-11T23:06:16.045639893<EFBFBD>U<EFBFBD>
<02><0F>GG<00>https://www.usenix.org/events/hotos11/tech/final_files/Kannan.pdfMaking Programs Forget: Enforcing Lifetime For Sensitive Data (2011)security/2017-09-11T23:06:16.0456398932017-09-11T23:06:16.045639893<EFBFBD>:<3A>
<02>UGG<00>https://www.usenix.org/system/files/conference/woot13/woot13-kholia.pdfLooking inside the (Drop) Box (2013)security/2017-09-11T23:06:16.0456398932017-09-11T23:06:16.045639893<EFBFBD>+<2B>	qcGG<00>https://internetcensus2012.bitbucket.io/paper.htmlInternet Census via Insecure Routers (2012)security/2017-09-11T23:06:16.0456398932017-09-11T23:06:16.045639893<EFBFBD>i<EFBFBD>~<02>!<21>+GG<00>https://rse-lab.cs.washington.edu/postscripts/3d-mapping-iser-10-final.pdfRGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environmentsrobotics/2017-09-11T23:06:16.0445410162017-09-11T23:06:16.044541016<EFBFBD><<3C>}
o<>GG<00>http://msl.cs.uiuc.edu/~lavalle/papers/Lav98c.pdfRapidly-Exploring Random Trees: A New Tool for Path Planningrobotics/2017-09-11T23:06:16.0445410162017-09-11T23:06:16.044541016
i<0E>
<0A>
En<0B>
U	<09><08><07><06><04>6s
<01>
i<00>&<26>"	=1GGhttp://www.cs.ox.ac.uk/people/nicolas.wu/papers/Scope.pdfEffect Handlers in Scopelanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>.<2E>!
<00>71GGhttp://www.cs.ru.nl/~W.Swierstra/Publications/DataTypesALaCarte.pdfData types a la cartelanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>*<2A> 	mW1GGhttp://okmij.org/ftp/Haskell/extensible/more.pdfFreer Monads, More Extensible Effectslanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>?<3F>	q}1GGhttp://okmij.org/ftp/Haskell/extensible/exteff.pdfExtensible Effects: An Alternative to Monad Transformerslanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>V<EFBFBD>
<00>7c1GGhttp://haskell.cs.yale.edu/wp-content/uploads/2011/02/POPL96-Modular-interpreters.pdfMonad Transformers and Modular Interpreterslanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>e<EFBFBD>
<00>aW1GGhttps://page.mi.fu-berlin.de/scravy/realworldhaskell/materialien/the-essence-of-functional-programming.pdfThe Essence of Functional Programminglanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD><1C>
<00>WO1GGhttps://ac.els-cdn.com/0890540191900524/1-s2.0-0890540191900524-main.pdf?_tid=45497e1c-b5c9-11e7-963f-00000aacb361&acdnat=1508526351_2f3bf288ce0f81ff89fb10ece92eeb9eNotions of Computation and Monadslanguages/haskell/2017-10-21T05:25:06.0342170412017-10-21T05:25:06.034217041<EFBFBD>3<EFBFBD>	iOOGGhttps://www.cs.cmu.edu/~rwh/theses/okasaki.pdfPurely Functional Data Structuresparadigms/functional_programming/2017-10-20T05:25:06.0079221192017-10-20T05:25:06.007922119<EFBFBD>:<3A>
c<>	'GGhttps://papers.mathyvanhoef.com/ccs2017.pdfKey Reinstallation Attacks: Forcing Nonce Reuse in WPA2 (2017)cryptography/2017-10-19T05:25:06.1591359862017-10-19T05:25:06.159135986<EFBFBD><0B><00><17>KQGGhttp://web.media.mit.edu/~minsky/papers/Why%20programming%20is--.htmlWhy Programming is a good medium for expressing poorly understood and sloppily-formulated ideascomp_sci_fundamentals_and_history/2017-10-04T05:25:05.8415810552017-10-04T05:25:05.841581055<EFBFBD>c<EFBFBD>
<00>uQGGhttp://www3.alcatel-lucent.com/bstj/vol34-1955/articles/bstj34-5-1045.pdfMealy, A Method for Synthesizing Sequential Circuitscomp_sci_fundamentals_and_history/2017-10-04T05:25:05.8415810552017-10-04T05:25:05.841581055<EFBFBD>M<EFBFBD>
g<>/GG

http://www.vmware.com/pdf/asplos235_adams.pdfA Comparison of Software and Hardware Techniques for x86
  Virtualizationvirtual_machines/2017-09-11T23:06:16.1364870612017-09-11T23:06:16.136487061<EFBFBD>6<EFBFBD>
<02>;/GG
http://lafo.ssw.uni-linz.ac.at/papers/2013_Onward_OneVMToRuleThemAll.pdfOne VM to Rule Them Allvirtual_machines/2017-09-11T23:06:16.1364870612017-09-11T23:06:16.136487061<EFBFBD>%<25>	C-CC
http://www.voelter.de/data/pub/projectingModuleFuture.pdfProjecting a modular futureuser_interfaces/2017-09-11T23:06:16.13565212017-09-11T23:06:16.1356521<EFBFBD>2<EFBFBD>	si-CC
	http://ordiecole.com/squeak/cardelli_squeak1985.pdfSqueak: a Language for Communicating with Miceuser_interfaces/2017-09-11T23:06:16.13565212017-09-11T23:06:16.1356521<EFBFBD>S<EFBFBD>
U<>G%GG
http://futuredata.stanford.edu/asap/ASAP: Automatic Smoothing for Attention Prioritization in Streaming Time Series Visualizationtime_series/2017-09-11T23:06:16.1183569342017-09-11T23:06:16.118356934<EFBFBD>0<EFBFBD>	Y%GG
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=208278Operators on Inhomogeneous Time Seriestime_series/2017-09-11T23:06:16.1183569342017-09-11T23:06:16.118356934<EFBFBD><EFBFBD><02><07>k%GG

http://www.msr-waypoint.net/en-us/groups/ese/nagappan_tdd.pdfRealizing quality improvement through test driven development: results and experiences of four industrial teamstesting/tdd/2017-09-11T23:06:16.1154199222017-09-11T23:06:16.115419922<EFBFBD><00>
<02>_1GG
http://www.elizabete.com.br/site/Outros/Entradas/2012/11/19_Revisao_Sistematica_files/ConceitosRevisaoSistematica_Biolchini.pdfSystematic Review in Software Engineeringsystematic_review/2017-09-11T23:06:16.0948500982017-09-11T23:06:16.094850098

Z,<00><0E>
l<0C>
8<0E><00>p<02><03><02><05><0C><00>E<0E>u%dZ'<0B><0B><07>_<04>
<EFBFBD>
<EFBFBD>
F
	<09><04>	`$7<07>	
<08><06>jf<03>D<04>	https://research.microsoft.com/en-us/um/people/nick/coqasm.pdf<00><><04>https://moodle.risc.jku.at/pluginfile.php/3407/mod_resource/content/1/A%20Calculus%20of%20Communicating%20Systems%5B1980%5D.pdf<00>#https://githu<68>I<04>https://github.com/tpn/pdfs/raw/master/Realizing%20Quality%20Improvement%20Through%20Test%20Driven%20Development%20-%20Results%20and%20Experiences%20of%20Four%20Industrial%20Teams%20(nagappan_tdd
*a<04>Chttps://www.tk.informatik.tu-darmstadt.de/fileadmin/user_upload/Group_TK/zhou2010survey.pdf
%O<04>https://people.cs.kuleuven.be/~tom.schrijvers/Research/papers/mpc2015.pdf
#p<04>ahttps://page.mi.fu-berlin.de/scravy/realworldhaskell/materialien/the-essence-of-functional-programming.pdf
3ihttps://www.cs.cmu.edu/~rwh/theses/okasaki.pdf
0chttps://papers.mathyvanhoef.com/ccs2017.pdf
M<04>https://www.usenix.org/system/files/conference/woot13/woot13-kholia.pdf
7qhttps://internetcensus2012.bitbucket.io/paper.html<00>P<04>!https://rse-lab.cs.washington.edu/postscripts/3d-mapping-iser-10-final.pdf<00>:whttps://www.cs.utah.edu/plt/publications/macromod.pdf<00>S<04>'https://www.seas.harvard.edu/sites/default/files/files/archived/Czaplicki.pdf<00>O<04>https://us-east.manta.joyent.com/bcantrill/public/ppwl-cantrill-zones.pdf<00>O<04>https://us-east.manta.joyent.com/bcantrill/public/ppwl-cantrill-jails.pdf<00>B<04>https://people.csail.mit.edu/nickolai/papers/clements-sc.pdf<00>a<04>Chttps://www.usenix.org/legacy/publications/library/proceedings/bos94/full_papers/bonwick.ps<00>`<04>Ahttps://www.usenix.org/legacy/publications/library/proceedings/bos94/full_papers/bonwick.a<00>W<04>/https://www.usenix.org/legacy/publications/library/proceedings/bos94/bonwick.html<00>
0https://cs.brown_<04>?https://irenelopatovska.files.wordpress.com/2012/10/lopatovska_arapakis_2011_theories.pdf
,G<04>https://www.usenix.org/events/hotos11/tech/final_files/Kannan.pdf

C<04>https://www.cs.princeton.edu/~chazelle/pubs/FJLT-sicomp09.pdf<00>A<04>https://www.stat.berkeley.edu/~breiman/randomforest2001.pdf<00>Q<04>#https://www.usenix.org/system/files/conference/osdi14/osdi14-paper-yuan.pdf<00>T<04>+
https://www.usenix.org/legacy/events/hotos03/tech/full_papers/candea/candea.pdfBR<04>'
https://www.usenix.org/legacy/event/osdi04/tech/full_papers/candea/candea.pdfC7qhttps://www.sics.se/~seif/DatalogiII/Book/train.ps<00>z<04>w
https://www.researchgate.net/publication/220080099_MEXICA_A_computer_model_of_a_cognitive_account_of_creative_writing2ghttps://www.lri.fr/~filliatr/publis/enum2.pdf<00>R<04>'
https://www.ics.uci.edu/~fielding/pubs/dissertation/fielding_dissertation.pdfD<04>
https://www.eecs.berkeley.edu/~daw/papers/intents-mobisys11.pdf=
https://www.cs.virginia.edu/~robins/Turing_Paper_1936.pdfB<04>
https://www.cs.unc.edu/~welch/kalman/media/pdf/Kalman1960.pdfKD<04>	https://www.cs.purdue.edu/homes/hosking/690M/p611-fenichel.pdf<00>K<04>
https://www.cs.drexel.edu/~david/Classes/CS586/Papers/p343-whitted.pdf 6ohttps://www.cs.cornell.edu/home/kleinber/auth.pdf<00><}
https://www.cs.cornell.edu/fbs/publications/SMSurvey.pdfp;yhttps://www.cs.cmu.edu/~dga/papers/epaxos-sosp2013.pdf<00>;{
https://people.eecs.berkeley.edu/~brewer/cs262/Mesa.pdf@S<04>)
https://homes.cs.washington.edu/~luisceze/publications/dnastorage-asplos16.pdf~
@%
https://github.com/papers-we-love/papers-we-love/blob/master/caching/a-constant-algorithm-for-implementing-the-lfu-cache-eviction-scheme.pdf<16><04>
https://github.com/papers-we-love/papers-we-love/blob/master/artificial_intelligence/3-bayesian-network-inference-algorithm.pdf9w
https://github.com/luanfujun/deep-p7https://osf.io/6qzxc/
0*Whttps://spectreattack.com/spectre.pdf
.,[https://meltdownattack.com/meltdown.pdf
-<2D><04>3https://github.com/papers-we-love/papers-we-love/blob/master/sublinear_algorithms/An-Elementary-Proof-of-a-Theorem-of-Johnson-and-Lindenstrauss.pdf
<00>
https://github.com/papers-we-love/papers-we-love/blob/master/sublinear_algorithms/1985-Flajolet-Probabilistic-counting.pdf

<00>
S8<00>
 In this work we thus present FlowDroid, a novel and highly precise static taint analysis for Android applications. A precise model of Android's lifecycle allows the analysis to properly handle callbacks invoked by the Android framework, while context, flow, field and object-sensitivity allows the analysis to reduce the number of false alarms. Novel on-demand algorithms help FlowDroid maintain high efficiency and precision at the same time.
 We also propose DroidBench, an open test suite for evaluating the effectiveness and accuracy of taint-analysis tools specifically for Android apps. As we show through a set of experiments using SecuriBench Micro, DroidBench, and a set of well-known Android test applications, FlowDroid finds a very high fraction of data leaks while keeping the rate of false positives low. On DroidBench, FlowDroid achieves 93% recall and 86% precision, greatly outperforming the commercial tools IBM AppScan Source and Fortify SCA. FlowDroid successfully finds leaks in a subset of 500 apps from Google Play and about 1,000 malware apps from the VirusShare project.PLDIandroid/2017-09-11T23:06:19.2972309572017-09-11T23:06:19.297230957<EFBFBD>*
<00><02>wUEEReverend Bayes on Inference Engines: A Distributed Hierarchical Approach<07>This paper presents generalizations of Bayes likelihood-ratio updating rule which facilitate an asynchronous propagation of the impacts of new beliefs and/or new evidence in hierarchically organized inference structures with multi-hypotheses variables. The computational scheme proposed specifies a set of belief parameters, communication messages and updating rules which guarantee that the diffusion of updated beliefs is accomplished in a single pass and complies with the tenets of Bayes calculus.AAAIartificial_intelligence/judea_pearl/2017-09-11T23:06:19.176239992017-09-11T23:06:19.17623999
<04>(<04><00>q
C<02>w=GGDirect and Indirect Effects<07>The direct effect of one event on another can be defined and measured by holding constant all intermediate variables between the two. Indirect effects present conceptual and prac­ tical difficulties (in nonlinear models), be­ cause they cannot be isolated by holding cer­ tain variables constant. This paper presents a new way of defining the effect transmit­ ted through a restricted set of paths, without controlling variables on the remaining paths. This permits the assessment of a more nat­ ural type of direct and indirect effects, one that is applicable in both linear and nonlinear models and that has broader policy-related interpretations. The paper establishes con­ ditions under which such assessments can be estimated consistently from experimen­ tal and nonexperimental data, and thus ex­ tends path-analytic techniques to nonlinear and nonparametric models. The distinction between total, direct, and indirect ef­ fects is deeply entrenched in causal conversations, and attains practical importance in many applications, in­ cluding policy decisions, legal definitions and health care analysis. Structural equation modeling (SEM) (Goldberger 1972), which provides a methodology of defining and estimating such effects, has been re­ stricted to linear analysis, and no comparable method­ ology has been devised to extend these capabilities to models involving nonlinear dependencies,1 as those 1 A notable exception is the counterfactual analysis of Robins and Greenland (1992) which is applicable to non­ linear models, but does not incorporate path-analytic tech­ niques. The causal relationship that is easiest to interpret, define and estimate is the total effect. Written as P(Y"' = y), the total effect measures the probability that response variable Y would take on the value y when X is set to x by external intervention.2 This probability function is what we normally assess in a controlled experiment in which X is randomized and in which the distribution of Y is estimated for each level x of X. In many cases, however, this quantity does not ade­ quately represent the target of investigation and at­ tention is focused instead on the direct effect of X on Y. The term "direct effect" is meant to quantify an influence that is not mediated by other variables in the model or, more accurately, the sensitivity of Y to changes in X while all other factors in the analysis are held fixed. Naturally, holding those factors fixed would sever all causal paths from X to Y with the exception of the direct link …UAIartificial_intelligence/2017-09-11T23:06:19.8314470212017-09-11T23:06:19.831447021<EFBFBD>U
<00>{

=GGAnalysis of Three Bayesian Network Inference Algorithms: Variable Elimination, Likelihood Weighting, and Gibbs Sampling<07>artificial_intelligence/2017-09-11T23:06:19.7328769532017-09-11T23:06:19.732876953

<EFBFBD><00>A
U<02>
=AAComputing Machinery and Intelligence<07>I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the 'imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart front the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B thus: C: Will X please tell me the length of his or her hair? Now suppose X is actually A, then A must answer. It is A's object in the game to try and cause C to make the wrong identification. His answer might therefore be: "My hair is shingled, and the longest strands are about nine inches long." In order that tones of voice may not help the interrogator the answers should be written, or better still, typewritten. The ideal arrangement is to have a teleprinter communicating between the two rooms. Alternatively the question and answers can be repeated by an intermediary. The object of the game for the third player (B) is to help the interrogator. The best strategy for her is probably to give truthful answers. She can add such things as "I am the woman, don't listen to him!" to her answers, but it will avail …artificial_intelligence/2017-09-11T23:06:19.9703752017-09-11T23:06:19.970375<EFBFBD>3
u<02>aGGAnalyzing inter-application communication in Android<07>Modern smartphone operating systems support the development of third-party applications with open system APIs. In addition to an open API, the Android operating system also provides a rich inter-application message passing system. This encourages inter-application collaboration and reduces developer burden by facilitating component reuse. Unfortunately, message passing is also an application attack surface. The content of messages can be sniffed, modified, stolen, or replaced, which can compromise user privacy. Also, a malicious application can inject forged or otherwise malicious messages, which can lead to breaches of user data and violate application security policies.
 We examine Android application interaction and identify security risks in application components. We provide a tool, ComDroid, that detects application communication vulnerabilities. ComDroid can be used by developers to analyze their own applications before release, by application reviewers to analyze applications in the Android Market, and by end users. We analyzed 20 applications with the help of ComDroid and found 34 exploitable vulnerabilities; 12 of the 20 applications have at least one vulnerability.MobiSysandroid/2017-09-11T23:06:19.8910729982017-09-11T23:06:19.891072998
<02>l<0B><06><02><00>!
I<02>;UGGA Theory of Inferred Causation<07>This paper concerns the empirical basis of causation, and addresses the following issues: 1. the clues that might prompt people to perceive causal relationships in uncontrolled observations. 2. the task of inferring causal models from these clues, and 3. whether the models inferred tell us anything useful about the causal mechanisms that underly the observations. We propose a minimal-model semantics of causation, and show that, contrary to common folklore, genuine causal innuences can be distinguished from spurious covariations following standard norms of inductive reasoning. We also establish a sound characterization of the conditions under which such a distinction is possible. We provide an effective algorithm for inferred causation and show that, for a large class of data the algorithm can uncover the direction of causal innuences as deened above. Finally, we address the issue of non-temporal causation.KRartificial_intelligence/judea_pearl/2017-09-11T23:06:20.4471569822017-09-11T23:06:20.447156982<EFBFBD>
<00><02>e=GGMastering the game of Go with deep neural networks and tree search<07>The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves. Here we introduce a new approach to computer Go that uses 'value networks' to evaluate board positions and 'policy networks' to select moves. These deep neural networks are trained by a novel combination of supervised learning from human expert games, and reinforcement learning from games of self-play. Without any lookahead search, the neural networks play Go at the level of state-of-the-art Monte Carlo tree search programs that simulate thousands of random games of self-play. We also introduce a new search algorithm that combines Monte Carlo simulation with value and policy networks. Using this search algorithm, our program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.Natureartificial_intelligence/2017-09-11T23:06:20.1121799322017-09-11T23:06:20.112179932<EFBFBD>	
<00>#

#GGArchitectural Styles and the Design of Network-based Software Architectures<07>api_design/2017-09-11T23:06:20.0495681152017-09-11T23:06:20.049568115<EFBFBD>
_<02>9GGSecurity Concerns in Android mHealth Apps<07>Mobile Health (mHealth) applications lie outside of regulatory protection such as HIPAA, which requires a baseline of privacy and security protections appropriate to sensitive medical data. However, mHealth apps, particularly those in the app stores for iOS and Android, are increasingly handling sensitive data for both professionals and patients. This paper presents a series of three studies of the mHealth apps in Google Play that show that mHealth apps make widespread use of unsecured Internet communications and third party servers. Both of these practices would be considered problematic under HIPAA, suggesting that increased use of mHealth apps could lead to less secure treatment of health data unless mHealth vendors make improvements in the way they communicate and store data.AMIAandroid/2017-09-11T23:06:20.0082419432017-09-11T23:06:20.008241943
<0C>	<09><04><00>[<00><02>/+GGThe BUDS Language for Distributed Bayesian Machine Learning<07>We describe BUDS, a declarative language for succinctly and simply specifying the implementation of large-scale machine learning algorithms on a distributed computing platform. The types supported in BUDS--vectors, arrays, etc.--are simply logical abstractions useful for programming, and do not correspond to the actual implementation. In fact, BUDS automatically chooses the physical realization of these abstractions in a distributed system, by taking into account the characteristics of the data. Likewise, there are many available implementations of the abstract operations offered by BUDS (matrix multiplies, transposes, Hadamard products, etc.). These are tightly coupled with the physical representation. In BUDS, these implementations are co-optimized along with the representation. All of this allows for the BUDS compiler to automatically perform deep optimizations of the user's program, and automatically generate efficient implementations.SIGMOD Conferenceaudio_comp_sci/2017-09-11T23:06:20.7854230962017-09-11T23:06:20.785423096<EFBFBD>E
m<02>

+GGEvaluating Generative Models for Text Generation<07>Generating human quality text is a challenging problem because of ambiguity of meaning and difficulty in modeling long term semantic connections. Recurrent Neural Networks (RNNs) have shown promising results in this problem domain, with the most common approach to its training being to maximize the log predictive likelihood of each true token in the training sequence given the previously observed tokens. Scheduled Sampling, proposed by Bengio et al. (2015), was proposed as an improvement to the maximum likelihood approach by stochastically introducing inference steps during training steps. More recently, Generative Adversarial Nets (GAN) that use a discriminative model to guide the training of the generative model have become popular in vision domain, and also reinterpreted as a reinforcement learning problem to adapt it to text generation by Yu et al. (2016). Here we test and compare these three approaches and thus hope to extend the evaluation presented for the SeqGAN model in Yu et al. (2016) using two additional datasets and an additional perplexity evaluation metric.audio_comp_sci/2017-09-11T23:06:20.7041730962017-09-11T23:06:20.704173096<EFBFBD>&
[<02>UoUGGThe algorithmization of counterfactuals<07>Recent advances in causal reasoning have given rise to a computation model that emulates the process by which humans generate, evaluate and distinguish counterfactual sentences. Though compatible with the “possible worlds” account, this model enjoys the advantages of representational economy, algorithmic simplicity and conceptual clarity. Using this model, the paper demonstrates the processing of counterfactual sentences on a classical example due to Ernest Adam. It then gives a panoramic view of several applications where counterfactual reasoning has benefited problem areas in the empirical sciences.Annals of Mathematics and Artificial Intelligenceartificial_intelligence/judea_pearl/2017-09-11T23:06:20.6384050292017-09-11T23:06:20.638405029<EFBFBD>/
Y<02>K
UGGCausal Diagrams for Empirical Research<07>The primary aim of this paper is to show how graphical models can be used as a mathematical language for integrating statistical and subject-matter information. In particular, the paper develops a principled, nonparametric framework for causal inference, in which diagrams are queried to determine if the assumptions available are suucient for identifying causal eeects from non-experimental data. If so the diagrams can be queried to produce mathematical expressions for causal eeects in terms of observed distributions; otherwise, the diagrams can be queried to suggest additional observations or auxiliary experiments from which the desired inferences can be obtained.artificial_intelligence/judea_pearl/2017-09-11T23:06:20.5518000492017-09-11T23:06:20.551800049
<03>
><03><00>*
g<02>['GGVEWS: A Wikipedia Vandal Early Warning System<07>We study the problem of detecting vandals on Wikipedia <i>before</i> any human or known vandalism detection system reports flagging potential vandals so that such users can be presented early to Wikipedia administrators. We leverage multiple classical ML approaches, but develop 3 novel sets of features. Our Wikipedia Vandal Behavior (WVB) approach uses a novel set of user editing patterns as features to classify some users as vandals. Our Wikipedia Transition Probability Matrix (WTPM) approach uses a set of features derived from a transition probability matrix and then reduces it via a neural net auto-encoder to classify some users as vandals. The VEWS approach merges the previous two approaches. Without using any information (e.g. reverts) provided by other users, these algorithms each have over 85% classification accuracy. Moreover, when temporal recency is considered, accuracy goes to almost 90%. We carry out detailed experiments on a new data set we have created consisting of about 33K Wikipedia users (including both a black list and a white list of editors) and containing 770K edits. We describe specific behaviors that distinguish between vandals and non-vandals. We show that VEWS beats ClueBot NG and STiki, the best known algorithms today for vandalism detection. Moreover, VEWS detects far more vandals than ClueBot NG and on average, detects them 2.39 edits before ClueBot NG when both detect the vandal. However, we show that the combination of VEWS and ClueBot NG can give a fully automated vandal early warning system with even higher accuracy.KDDbiocomputing/2017-09-11T23:06:20.9852609862017-09-11T23:06:20.985260986<EFBFBD>?
c<02>+GGSafety Verification of Deep Neural Networks<07>Deep neural networks have achieved impressive experimental results in image classification, but can surprisingly be unstable with respect to adver-sarial perturbations, that is, minimal changes to the input image that cause the network to misclassify it. With potential applications including perception modules and end-to-end controllers for self-driving cars, this raises concerns about their safety. We develop the first SMT-based automated verification framework for feed-forward multi-layer neural networks that works directly with the code of the network, exploring it layer by layer. We define safety for a region around a data point in a given layer by requiring that all points in the region are assigned the same class label. Working with a notion of a manipulation, a mapping between points that intuitively corresponds to a modification of an image, we employ discretisation to enable exhaustive search of the region. Our method can guarantee that adversarial examples are found for the given region and set of manipulations. If found, adversarial examples can be shown to human testers and/or used to fine-tune the network, and otherwise the network is declared safe for the given parameters. We implement the techniques using Z3 and evaluate them on state-of-the-art networks, including regularised and deep learning networks.CAVaudio_comp_sci/2017-09-11T23:06:20.8417080082017-09-11T23:06:20.841708008
<03>H
YZ<03><00>y]<02>q<EFBFBD>-GGBIG Cache Abstraction for Cache Networks<07>In this paper, we advocate the notion of &#x0022;BIG&#x0022; cache as an innovative abstraction for effectively utilizing the distributed storage and processing capacities of all servers in a cache network. The &#x0022;BIG&#x0022; cache abstraction is proposed to partly address the problem of (cascade) thrashing in a hierarchical network of cache servers, where it has been known that cache resources at intermediate servers are poorly utilized, especially under classical cache replacement policies such as LRU. We lay out the advantages of &#x0022;BIG&#x0022; cache abstraction and make a strong case both from a theoretical standpoint as well as through simulation analysis. We also develop the dCLIMB cache algorithm to minimize the overheads of moving objects across distributed cache boundaries and present a simple yet effective heuristic for addressing the cache allotment problem in the design of &#x0022;BIG&#x0022; cache abstraction.2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)caching/2017-09-11T23:06:21.4933010252017-09-11T23:06:21.493301025<EFBFBD>|
S<02>
'GGThe chemical basis of morphogenesis<07>Concurrent algorithms and the memory bus have garnered improbable interest from both theorists and futurists in the last several years. In fact, few scholars would disagree with the refinement of multicast heuristics. In order to fulfill this objective, we present a framework for virtual technology (Puck), confirming that lambda calculus can be made wearable, self-learning, and unstable.biocomputing/2017-09-11T23:06:21.2694760742017-09-11T23:06:21.269476074<EFBFBD>l<00><02>5'GGMolecular computation of solutions to combinatorial problems.<07>The tools of molecular biology were used to solve an instance of the directed Hamiltonian path problem. A small graph was encoded in molecules of DNA, and the "operations" of the computation were performed with standard protocols and enzymes. This experiment demonstrates the feasibility of carrying out computations at the molecular level.Sciencebiocomputing/2017-09-11T23:06:21.2355869142017-09-11T23:06:21.235586914<EFBFBD>5
A<02>y-+GGInteractive topic modeling<07>Topic models are a useful and ubiquitous tool for understanding large corpora. However, topic models are not perfect, and for many users in computational social science, digital humanities, and information studies—who are not machine learning experts—existing models and frameworks are often a “take it or leave it” proposition. This paper presents a mechanism for giving users a voice by encoding users’ feedback to topic models as correlations between words into a topic model. This framework, interactive topic modeling (itm), allows untrained users to encode their feedback easily and iteratively into the topic models. Because latency in interactive systems is crucial, we develop more efficient inference algorithms for tree-based topic models. We validate the framework both with simulated and real users.Machine Learningaudio_comp_sci/2017-09-11T23:06:21.1205358892017-09-11T23:06:21.120535889

<01><0B>
<01><00>^<00>#<02>
GG2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm<07>In a path-breaking paper last year Pat and Betty O'Neil and Gerhard Weikum proposed a self-tuning improvement to the Least Recently Used (LRU) buuer management algorithmm15]. Their improvement is called LRU/k and advocates giving priority to buuer pages based on the kth most recent access. (The standard LRU algorithm is denoted LRU/1 according to this terminology.) If P1's kth most recent access is more more recent than P2's, then P1 will be replaced after P2. Intuitively, LRU/k for k > 1 is a good strategy , because it gives low priority to pages that have been scanned or to pages that belong to a big randomly accessed le (e.g., the account le in TPC/A). They found that LRU/2 achieves most of the advantage of their method. The one problem of LRU/2 is the processor overhead to implement it. In contrast to LRU, each page access requires log N work to manipulate a priority queue where N is the number of pages in the buuer. Question: is there low overhead way (constant overhead per access as in LRU) to achieve similar page 0 replacement performance to LRU/2? Answer: Yes. Our \Two Queue" algorithm (hereafter 2Q) has constant time overhead, performs as well as LRU/2, and requires no tuning. These results hold for real (DB2 commercial, Swiss bank) traces as well as simulated ones. Based on these experiments, we estimate that 2Q will provide a few percent improvement over LRU without increasing the overhead by more than a constant additive factor. 1 Background Fetching data from disk requires at least a factor of 1000 more time than fetching data from a RAM buuer. For this reason, good use of the buuer can signii-cantly improve the throughput and response time of any data-intensive system. Until the early 80's, the least recently used buuer replacement algorithm (replace the page that was least recently accessed or used) was the algorithm of choice in nearly all cases. Indeed, the theoretical community blessed it by showing that LRU never replaces more than a factor B as many elements as an optimal clair-voyant algorithm (where B is the size of the buuer) 19]. 1 Factors this large can heavily innuence the behavior of a database system, however. Furthermore , database systems usually have access patterns in which LRU performs poorly, as noted by Stone-braker 21], Sacco and Schkolnick 18], and Chou and Dewitt 5]. As a result, there …VLDBcaching/2017-09-11T23:06:21.6556608892017-09-11T23:06:21.655660889<EFBFBD>q
S<02>w'GGA DNA-Based Archival Storage System<07>Demand for data storage is growing exponentially, but the capacity of existing storage media is not keeping up. Using DNA to archive data is an attractive possibility because it is extremely dense, with a raw limit of 1 exabyte/mm<sup>3</sup> (109 GB/mm<sup>3</sup>), and long-lasting, with observed half-life of over 500 years. This paper presents an architecture for a DNA-based archival storage system. It is structured as a key-value store, and leverages common biochemical techniques to provide random access. We also propose a new encoding scheme that offers controllable redundancy, trading off reliability for density. We demonstrate feasibility, random access, and robustness of the proposed encoding with wet lab experiments involving 151 kB of synthesized DNA and a 42 kB random-access subset, and simulation experiments of larger sets calibrated to the wet lab experiments. Finally, we highlight trends in biotechnology that indicate the impending practicality of DNA storage for much larger datasets.ASPLOSbiocomputing/2017-09-11T23:06:21.5554060062017-09-11T23:06:21.555406006
W<0C>	<09>5W<00>[<00><02>CG?GGMEXICA: A computer model of a cognitive account of creative writing<07>MEXICA is a computer model that produces frameworks for short stories based on the engagement-reflection cognitive account of writing. During engagement MEXICA generates material guided by content and rhetorical constraints, avoiding the use of explicit goals or story-structure information. During reflection the system breaks impasses, evaluates the novelty and interestingness of the story in progress and verifies that coherence requirements are satisfied. In this way, MEXICA complements and extends those models of computerised story-telling based on traditional problem-solving techniques where explicit goals drive the generation of stories. This paper describes the engagement-reflection account of writing, the general characteristics of MEXICA and reports an evaluation of the programJ. Exp. Theor. Artif. Intell.computational_creativity/2017-09-11T23:06:22.0232080082017-09-11T23:06:22.023208008<EFBFBD>&<00><02>;GGA program optimization for automatic database result caching<07>Most popular Web applications rely on persistent databases based on languages like SQL for declarative specification of data models and the operations that read and modify them. As applications scale up in user base, they often face challenges responding quickly enough to the high volume of requests. A common aid is caching of database results in the application&#039;s memory space, taking advantage of program-specific knowledge of which caching schemes are sound and useful, embodied in handwritten modifications that make the program less maintainable. These modifications also require nontrivial reasoning about the read-write dependencies across operations. In this paper, we present a compiler optimization that automatically adds sound SQL caching to Web applications coded in the Ur/Web domain-specific functional language, with no modifications required to source code. We use a custom cache implementation that supports concurrent operations without compromising the transactional semantics of the database abstraction. Through experiments with microbenchmarks and production Ur/Web applications, we show that our optimization in many cases enables an easy doubling or more of an application&#039;s throughput, requiring nothing more than passing an extra command-line flag to the compiler.POPLcaching/2017-09-11T23:06:21.9159089362017-09-11T23:06:21.915908936<EFBFBD>

k<02>
9GGOn the resemblance and containment of documents<07>Given two documents A and B we define two mathematical notions: their resemblance r(A, B) and their containment c(A, B) that seem to capture well the informal notions of " roughly the same " and " roughly contained. " The basic idea is to reduce these issues to set intersection problems that can be easily evaluated by a process of random sampling that can be done independently for each document. Furthermore, the resemblance can be evaluated using a fixed size sample for each document. This paper discusses the mathematical properties of these measures and the efficient implementation of the sampling process using Rabin fingerprints.clustering_algorithms/2017-09-11T23:06:21.8212780762017-09-11T23:06:21.821278076<EFBFBD><00><02>U
QGGOn computable numbers with an application to the Entscheidungsproblem<07>Many cyberneticists would agree that, had it not been for consistent hashing, the simulation of checksums might never have occurred. After years of essential research into replication, we prove the analysis of online algorithms, which embodies the confirmed principles of robotics. Our focus in our research is not on whether digital-to-analog converters and evolutionary programming can agree to accomplish this mission, but rather on constructing a novel framework for the construction of scatter/gather I/O (HOLLEE). while such a hypothesis is usually an intuitive objective, it is derived from known results.comp_sci_fundamentals_and_history/2017-09-11T23:06:21.7456589362017-09-11T23:06:21.745658936
<03>
<0A>4<03><00>#
<00>#

1GGDigital Video Stabilization and Rolling Shutter Correction using Gyroscopes<07>computer_graphics/2017-09-11T23:06:22.2824418952017-09-11T23:06:22.282441895<EFBFBD><00><02>q
9GGPiranha: A scalable architecture based on single-chip multiprocessing<07>The microprocessor industry is currently struggling with higher development costs and longer design times that arise from exceedingly complex processors that are pushing the limits of instruction-level parallelism. Meanwhile, such designs are especially ill suited for important commercial applications, such as on-line transaction processing (OLTP), which suffer from large memory stall times and exhibit little instruction-level parallelism. Given that commercial applications constitute by far the most important market for high-performance servers, the above trends emphasize the need to consider alternative processor designs that specifically target such workloads. The abundance of explicit thread-level parallelism in commercial workloads, along with advances in semiconductor integration density, identify chip multiprocessing (CMP) as potentially the most promising approach for designing processors targeted at commercial servers. This paper describes the Piranha system, a research prototype being developed at Compaq that aggressively exploits chip multi-processing by integrating eight simple Alpha processor cores along with a two-level cache hierarchy onto a single chip. Piranha also integrates further on-chip functionality to allow for scalable multiprocessor configurations to be built in a glueless and modular fashion. The use of simple processor cores combined with an industry-standard ASIC design methodology allow us to complete our prototype within a short time-frame, with a team size and investment that are an order of magnitude smaller than that of a commercial microprocessor. Our detailed simulation results show that while each Piranha processor core is substantially slower than an aggressive next-generation processor, the integration of eight cores onto a single chip allows Piranha to outperform next-generation processors by up to 2.9 times (on a per chip basis) on important workloads such as OLTP. This performance advantage can approach a factor of five by using full-custom instead of ASIC logic. In addition to exploiting chip multiprocessing, the Piranha prototype incorporates several other unique design choices including a shared second-level cache with no inclusion, a highly optimized cache coherence protocol, and a novel I/O architecture.computer_architecture/2017-09-11T23:06:22.1723798832017-09-11T23:06:22.172379883<EFBFBD>2
S
<0A>_
QGGObject Space Silhouette AlgorithimsIn computer graphics, silhouette extraction and rendering has a critical role in a growing number of applications. This paper examines five object space silhouette extraction algorithms for polygonal models. The algorithms are applied to a variety of models and compared in terms of code complexity and run time performance. The purpose of this paper is to inform programmers who must choose from among these five algorithms.comp_sci_fundamentals_and_history/2017-09-11T23:06:22.0886579592017-09-11T23:06:22.088657959

<01>	<09><05>
<01><00>j"
e<02>C#1GGIllumination for Computer Generated Pictures<07>The quality of computer generated images of three-dimensional scenes depends on the shading technique used to paint the objects on the cathode-ray tube screen. The shading algorithm itself depends in part on the method for modeling the object, which also determines the hidden surface algorithm. The various methods of object modeling, shading, and hidden surface removal are thus strongly interconnected. Several shading techniques corresponding to different methods of object modeling and the related hidden surface algorithms are presented here. Human visual perception and the fundamental laws of optics are considered in the development of a shading rule that provides better quality and increased realism in generated images.Commun. ACMcomputer_graphics/2017-09-11T23:06:23.0423911132017-09-11T23:06:23.042391113<EFBFBD>!	W
71GGContinuous Shading of Curved Surfaces<07>IEEE Trans. Computerscomputer_graphics/2017-09-11T23:06:22.9449960942017-09-11T23:06:22.944996094<EFBFBD> 
o<02>
-1GGAn improved illumination model for shaded display<07>To accurately render a scene, global illumination information that affects the intensity of each pixel of the image must be known at the time the intensity is calculated. In a simplified form, this information is stored in a tree of &#8220;rays&#8221; extending from the viewer to the first surface encountered and from there to other surfaces and to the light sources. The visible surface algorithm creates this tree for each pixel of the display and passes it to the shader. The shader then traverses the tree to determine the intensity of the light received by the viewer. Consideration of all of these factors allows the shader to accurately simulate true reflection, shadows, and refraction as well as the effects simulated by conventional shaders. Anti-aliasing is included as an integral part of the visibility calculations. Surfaces displayed include curved as well as polygonal surfaces.SIGGRAPH Coursescomputer_graphics/2017-09-11T23:06:22.6666889652017-09-11T23:06:22.666688965<EFBFBD>1<00>#<02>1GGGigaVoxels: ray-guided streaming for efficient and detailed voxel rendering<07>We propose a new approach to efficiently render large volumetric data sets. The system achieves interactive to real-time rendering performance for several billion voxels.
 Our solution is based on an adaptive data representation depending on the current view and occlusion information, coupled to an efficient ray-casting rendering algorithm. One key element of our method is to guide data production and streaming directly based on information extracted during rendering.
 Our data structure exploits the fact that in CG scenes, details are often concentrated on the interface between free space and clusters of density and shows that volumetric models might become a valuable alternative as a rendering primitive for real-time applications. In this spirit, we allow a quality/performance trade-off and exploit temporal coherence. We also introduce a mipmapping-like process that allows for an increased display rate and better quality through high quality filtering. To further enrich the data set, we create additional details through a variety of procedural methods.
 We demonstrate our approach in several scenarios, like the exploration of a 3D scan (8192<sup>3</sup> resolution), of hypertextured meshes (16384<sup>3</sup> virtual resolution), or of a fractal (theoretically infinite resolution). All examples are rendered on current generation hardware at 20--90 fps and respect the limited GPU memory budget.SI3Dcomputer_graphics/2017-09-11T23:06:22.5203469242017-09-11T23:06:22.520346924
<00>yT<00><00>5%/<02>+<2B>1GGDeep Colorization<07>This paper investigates into the colorization problem which converts a grayscale image to a colorful version. This is a very difficult problem and normally requires manual adjustment to achieve artifact-free quality. For instance, it normally requires human-labelled color scribbles on the grayscale target image or a careful selection of colorful reference images (e.g., capturing the same scene in the grayscale target image). Unlike the previous methods, this paper aims at a high-quality fully-automatic colorization method. With the assumption of a perfect patch matching technique, the use of an extremely large-scale reference database (that contains sufficient color images) is the most reliable solution to the colorization problem. However, patch matching noise will increase with respect to the size of the reference database in practice. Inspired by the recent success in deep learning techniques which provide amazing modeling of large-scale data, this paper re-formulates the colorization problem so that deep learning techniques can be directly employed. To ensure artifact-free quality, a joint bilateral filtering based post-processing step is proposed. Numerous experiments demonstrate that our method outperforms the state-of-art algorithms both in terms of quality and speed.2015 IEEE International Conference on Computer Vision (ICCV)computer_graphics/2017-09-11T23:06:24.3129270022017-09-11T23:06:24.312927002<EFBFBD>"$
}<02>/1GG3-Sweep: extracting editable objects from a single photo<07>We introduce an interactive technique for manipulating simple 3D shapes based on extracting them from a single photograph. Such extraction requires understanding of the components of the shape, their projections, and relations. These simple cognitive tasks for humans are particularly difficult for automatic algorithms. Thus, our approach combines the cognitive abilities of humans with the computational accuracy of the machine to solve this problem. Our technique provides the user the means to quickly create editable 3D parts---human assistance implicitly segments a complex object into its components, and positions them in space. In our interface, three strokes are used to generate a 3D component that snaps to the shape's outline in the photograph, where each stroke defines one dimension of the component. The computer reshapes the component to fit the image of the object in the photograph as well as to satisfy various inferred geometric constraints imposed by its global 3D structure. We show that with this intelligent interactive modeling tool, the daunting task of object extraction is made simple. Once the 3D object has been extracted, it can be quickly edited and placed back into photos or 3D scenes, permitting object-driven photo editing tasks which are impossible to perform in image-space. We show several examples and present a user study illustrating the usefulness of our technique.ACM Trans. Graph.computer_graphics/2017-09-11T23:06:24.1674741212017-09-11T23:06:24.167474121<EFBFBD>#
I<02>iM1GGPoisson surface reconstruction<07>We show that surface reconstruction from oriented points can be cast as a spatial Poisson problem. This Poisson formulation considers all the points at once, without resorting to heuristic spatial partitioning or blending, and is therefore highly resilient to data noise. Unlike radial basis function schemes, our Poisson approach allows a hierarchy of locally supported basis functions, and therefore the solution reduces to a well conditioned sparse linear system. We describe a spatially adaptive multiscale algorithm whose time and space complexities are proportional to the size of the reconstructed model. Experimenting with publicly available scan data, we demonstrate reconstruction of surfaces with greater detail than previously achievable.Symposium on Geometry Processingcomputer_graphics/2017-09-11T23:06:23.9461679692017-09-11T23:06:23.946167969
W<0B><08>}W<00>#)
/<02>a-1GGBlue native PAGE.<07>Blue native PAGE (BN-PAGE) can be used for one-step isolation of protein complexes from biological membranes and total cell and tissue homogenates. It can also be used to determine native protein masses and oligomeric states and to identify physiological protein-protein interactions. Native complexes are recovered from gels by electroelution or diffusion and are used for 2D crystallization and electron microscopy or analyzed by in-gel activity assays or by native electroblotting and immunodetection. In this protocol, we describe methodology to perform BN-PAGE followed by (i) native extraction or native electroblotting of separated proteins, or (ii) a second dimension of tricine-SDS-PAGE or modified BN-PAGE, or (iii) a second dimension of isoelectric focusing (IEF) followed by a third dimension of tricine-SDS-PAGE for the separation of subunits of complexes. These protocols for 2D and 3D PAGE can be completed in 2 and 3 days.Nature protocolscomputer_graphics/2017-09-11T23:06:24.5827900392017-09-11T23:06:24.582790039<EFBFBD>?(
9<02>1GGThe rendering equation<07>We present an integral equation which generalizes a variety of known rendering algorithms. In the course of discussing a monte carlo solution we also present a new form of variance reduction, called Hierarchical sampling and give a number of elaborations shows that it may be an efficient new technique for a wide variety of monte carlo procedures. The resulting rendering algorithm extends the range of optical phenomena which can be effectively simulated.SIGGRAPHcomputer_graphics/2017-09-11T23:06:24.5243210452017-09-11T23:06:24.524321045<EFBFBD>'
m<02>/1GGWeb page classification: Features and algorithms<07>Classification of Web page content is essential to many tasks in Web information retrieval such as maintaining Web directories and focused crawling. The uncontrolled nature of Web content presents additional challenges to Web page classification as compared to traditional text classification, but the interconnected nature of hypertext also provides features that can assist the process.
 As we review work in Web page classification, we note the importance of these Web-specific features and algorithms, describe state-of-the-art practices, and track the underlying assumptions behind the use of information from neighboring pages.ACM Comput. Surv.computer_graphics/2017-09-11T23:06:24.4608410642017-09-11T23:06:24.460841064<EFBFBD>)&<00>7<02>{1GGKinectFusion: real-time 3D reconstruction and interaction using a moving depth camera<07>KinectFusion enables a user holding and moving a standard Kinect camera to rapidly create detailed 3D reconstructions of an indoor scene. Only the depth data from Kinect is used to track the 3D pose of the sensor and reconstruct, geometrically precise, 3D models of the physical scene in real-time. The capabilities of KinectFusion, as well as the novel GPU-based pipeline are described in full. Uses of the core system for low-cost handheld scanning, and geometry-aware augmented reality and physics-based interactions are shown. Novel extensions to the core GPU pipeline demonstrate object segmentation and user interaction directly in front of the sensor, without degrading camera tracking or reconstruction. These extensions are used to enable real-time multi-touch interactions anywhere, allowing any planar or non-planar reconstructed physical surface to be appropriated for touch.UISTcomputer_graphics/2017-09-11T23:06:24.3660039062017-09-11T23:06:24.366003906
p<00><0F><0F><0F>tW0<0E><0E><0E>{`D
<0A>
<0A>
<0A>
o
R
-
<0C><0C><0C>qX0<0B><0B><0B>b-
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
e
7
	<09>	<09>	<09>	<09>	_	>	<08><08><08><08>n@)<07><07><07><07>W0<06><06><06><06>{X5<05><05><05><05>jD)<04><04><04>sT7<03><03><03><03>uR+<02><02><02>vQ2
<01>
<01>
<01>
<01>
e
L
+
<00>!p)
Otmar HilligesOtmarHilligeso
David KimDavidKimn'
Shahram IzadiShahramIzadim
Bin ShengBinSheng!l)
Qingxiong YangQingxiongYangk%
Zezhou ChengZezhouCheng#j+
Daniel Cohen-OrDanielCohen-Ori!
Shi-Min HuShi-MinHuh%
Ariel ShamirArielShamirg
Zhe ZhuZheZhuf
Tao ChenTaoChene%
Hugues HoppeHuguesHoppe#d+
Matthew BolithoMatthewBolitho(c1Michael M. KazhdanMichaelM.Kazhdan"b+Bui Tuong PhongBuiTuongPhonga'
Henri GouraudHenriGouraud!`)
Turner WhittedTurnerWhitted!_)
Elmar EisemannElmarEisemann%^-
Sylvain LefebvreSylvainLefebvre!])
Fabrice NeyretFabriceNeyret\'
Cyril CrassinCyrilCrassin[#
Salim VirjiSalimVirjiZ!
Marc LevoyMarcLevoyY%
Jongmin BaekJongminBaekX%
David JacobsDavidJacobs)W1
Alexandre KarpenkoAlexandreKarpenkoV#
Bruce GoochBruceGoochU%
Elaine CohenElaineCohenT%
Mark HartnerMarkHartner!S)
Ashley HartnerAshleyHartnerR'
Mike SharplesMikeSharples0Q9Rafael Pérez Y PérezRafaelPérez YPérezP'
Adam ChlipalaAdamChlipalaO!
Ziv ScullyZivScully$N-Andrei Z. BroderAndreiZ.BroderM'
Dennis ShashaDennisShasha%L-
Theodore JohnsonTheodoreJohnsonK'
Karin StraussKarinStraussJ%
Georg SeeligGeorgSeeligI
Luis CezeLuisCeze(H1Douglas M. CarmeanDouglasM.Carmean!G)
Randolph LopezRandolphLopez!F)
James BornholtJamesBornholtE!
Gong ZhangGongZhangD
Runhui LiRunhuiLiC%
Zhi-Li ZhangZhi-LiZhang%B-
Arvind NarayananArvindNarayananA%
Eman RamadanEmanRamadan@#L M AdlemanLMAdleman%?-
Brianna SatinoffBriannaSatinoff.>7#Jordan L. Boyd-GraberJordanL.Boyd-Graber=!
Yuening HuYueningHu(<1%V. S. SubrahmanianV.S.Subrahmanian);1
Francesca SpezzanoFrancescaSpezzano:%
Srijan KumarSrijanKumar9
Min WuMinWu8
Sen WangSenWang,75#Marta Z. KwiatkowskaMartaZ.Kwiatkowska6'
Xiaowei HuangXiaoweiHuang!5)
Chris JermaineChrisJermaine*43Luis Leopoldo PerezLuisLeopoldoPerez3#
Shangyu LuoShangyuLuo2%Zekai J. GaoZekaiJ.Gao#1+
Suvrat BhooshanSuvratBhooshan0'
Raunaq RewariRaunaqRewari%/-
Prasad KawthekarPrasadKawthekar.%
Thomas VermaThomasVerma!-)
Demis HassabisDemisHassabis,'
Thore GraepelThoreGraepel'+/
#Koray KavukcuogluKorayKavukcuoglu#*+
Madeleine LeachMadeleineLeach,)5Timothy P. LillicrapTimothyP.Lillicrap!()
Ilya SutskeverIlyaSutskever%'-
%Nal KalchbrennerNalKalchbrenner&
John NhamJohnNham%'
Dominik GreweDominikGrewe#$+
Sander DielemanSanderDieleman#%
Marc LanctotMarcLanctot3";
)Vedavyas PanneershelvamVedavyasPanneershelvam)!1
!Ioannis AntonoglouIoannisAntonoglou- 5
'Julian SchrittwieserJulianSchrittwieser4=George Van Den DriesscheGeorgeVan DenDriessche'
Laurent SifreLaurentSifre#
Arthur GuezArthurGuez&/Chris J. MaddisonChrisJ.Maddison
Aja HuangAjaHuang%
David SilverDavidSilver(1David S. RosenblumDavidS.Rosenblum*3Roy Thomas FieldingRoyThomasFielding#+
Klara NahrstedtKlaraNahrstedt )Carl A. GunterCarlA.Gunter#+
Muhammad NaveedMuhammadNaveed#
Dongjing HeDongjingHe%A. M. TuringA.M.Turing"+David A. WagnerDavidA.Wagner!)
Kate GreenwoodKateGreenwood,5Adrienne Porter FeltAdriennePorterFelt!
Erika ChinErikaChin%-
Rusmin SoetjiptoRusminSoetjipto
#Rose F. LiuRoseF.Liu!
Somesh JhaSomeshJha%-
Patrick McdanielPatrickMcdaniel*
3Patrick D. McdanielPatrickD.Mcdaniel	'
Damien OcteauDamienOcteau'Yves Le TraonYvesLeTraon'
Jacques KleinJacquesKlein%-
Alexandre BartelAlexandreBartel#
Eric BoddenEricBodden#+
Christian FritzChristianFritz+3
Siegfried RasthoferSiegfriedRasthofer#
Steven ArztStevenArzt
#
Judea PearlJudeaPearl
j<00><0F><0F><0F>kL)
<0E><0E><0E>jM&
<0A>
<0A>
<0A>
<0A>
l
E
'
	<0C><0C><0C><0C>a2
<0B><0B><0B>{\<
<EFBFBD>
<EFBFBD>
<EFBFBD>
~
Y
=
	<09>	<09>	<09>	<09>	_	;	<08><08><08>lN,<07><07><07>vX><06><06><06><06>gK"<05><05><05><05>mO+<04><04><04>oU3<03><03><03>q5<02><02><02>|^@

<01>
<01>
<01>
<01>
O
1

<00><17>Z
Cory HillCoryHill!<21>Y)!
Sabyasachi RoySabyasachiRoy<1B>X#
Wyatt LloydWyattLloyd1<64>W9!
#Muralidhar SubramanianMuralidharSubramanian#<23>V+
Per-Åke LarsonPer-ÅkeLarson<1F>U'
Moran TzafrirMoranTzafrir<19>T!
Nir ShavitNirShavit#<23>S+
Maurice HerlihyMauriceHerlihy0<79>R9Flemming Friche RodlerFlemmingFricheRodler<1B>Q#
Rasmus PaghRasmusPagh<1B>P#
Tiark RompfTiarkRompf<1D>O%
Phil BagwellPhilBagwell<1B>N#
Pat HellandPatHelland#<23>M+
Matti PitkänenMattiPitkänen4<6E>L=!Christine Van VredendaalChristineVanVredendaal<1B>K#
Tanja LangeTanjaLange9<65>JA!
+Chitchanok ChuengsatiansupChitchanokChuengsatiansup*<2A>I3Daniel J. BernsteinDanielJ.Bernstein&<26>H/Martin E. HellmanMartinE.Hellman%<25>G-
Whitfield DiffieWhitfieldDiffie#<23>F+
Phillip RogawayPhillipRogaway<1B>E#
Eran TromerEranTromer<1F>D'
Daniel GenkinDanielGenkin<17>C
Erik TewsErikTews$<24>B-Michael L. ScottMichaelL.Scott$<24>A-Maged M. MichaelMagedM.Michael(<28>@1Leonard M. AdlemanLeonardM.Adleman<19>?!
Adi ShamirAdiShamir$<24>>-Ronald L. RivestRonaldL.Rivest!<21>=)
Leslie LamportLeslieLamport<1B><#
Armando FoxArmandoFox<1F>;'
Greg FriedmanGregFriedman<1F>:'
Yuichi FujikiYuichiFujiki'<27>9/
Shinichi KawamotoShinichiKawamoto<1F>8'
George CandeaGeorgeCandea"<22>7+David D. RedellDavidD.Redell&<26>6/Butler W. LampsonButlerW.Lampson<19>5!
Rob ArthanRobArthan<1D>4%
Konrad SlindKonradSlind<1F>3'
John HarrisonJohnHarrison%<25>2-
Richard CarlssonRichardCarlsson<1D>1%
Jade AlglaveJadeAlglave$<24>0-Magnus O. MyreenMagnusO.Myreen#<23>/+
Thomas BraibantThomasBraibant<17>.
Tom RidgeTomRidge<1B>-#
Scott OwensScottOwens4<73>,=Francesco Zappa NardelliFrancescoZappaNardelli<1D>+%
Peter SewellPeterSewell<1F>*'
Susmit SarkarSusmitSarkar<1C>)%Ulf T. WigerUlfT.Wiger<1B>(#
Thomas ArtsThomasArts<1F>''
Hans SvenssonHansSvensson<1B>&#
John HughesJohnHughes)<29>%1
Nicholas SmallboneNicholasSmallbone"<22>$+Michal H. PalkaMichalH.Palka<1F>#'
Koen ClaessenKoenClaessen)<29>"1
#Jesper WilhelmssonJesperWilhelmsson-<2D>!5%
Konstantinos SagonasKonstantinosSagonas!<21> )
Erik JohanssonErikJohansson-<2D>5
!Vasileios TrigonakisVasileiosTrigonakis%<25>-
Rachid GuerraouiRachidGuerraoui<1B>#
Tudor DavidTudorDavid%<25>-
Valerio PascucciValerioPascucci<1F>'
Julien TiernyJulienTierny<1B>#
Brian SummaBrianSumma<19>!
Bob SumnerBobSumner"<22>+Markus H. GrossMarkusH.Gross$<24>-Robert W. SumnerRobertW.Sumner#<23>+
Steve MarschnerSteveMarschner&<26>/Paul A. BeardsleyPaulA.Beardsley%<25>-!
Gioacchino NorisGioacchinoNoris<1D>%
Bernd BickelBerndBickel<1D>%
Thabo BeelerThaboBeeler<1C>%Luc Van GoolLucVanGool<1F>'
Andreas UlmerAndreasUlmer<1F>'
Simon HaeglerSimonHaegler(<28>1Leith Casey LeedomLeithCaseyLeedom<1D>
%
Brian CabralBrianCabral%<25>-
William RibarskyWilliamRibarsky,<2C>5François X. SillionFrançoisX.Sillion!<21>
)
Michael WimmerMichaelWimmer<19>	!
James GipsJamesGips<1D>%
George StinyGeorgeStiny!<21>)
Sanni SiltanenSanniSiltanen!<21>)
Pascal MüllerPascalMüller<1B>#
Peter WonkaPeterWonka<1B>#
Markus LippMarkusLipp$<24>-Michael F. CohenMichaelF.Cohen*<2A>3!Peter-Pike J. SloanPeter-PikeJ.Sloan#<23>
+
Anton KaplanyanAntonKaplanyan<1B>#
Helmut SiesHelmutSies'Dean P. JonesDeanP.Jones'~/
Hermann SchäggerHermannSchägger%}-!
Hans-Peter BraunHans-PeterBraun|#
Ilka WittigIlkaWittig"{+James T. KajiyaJamesT.Kajiya$z-Brian D. DavisonBrianD.Davisony%
Xiaoguang QiXiaoguangQi,x5!Andrew W. FitzgibbonAndrewW.Fitzgibbon&w/Andrew J. DavisonAndrewJ.Davison!v)
Dustin FreemanDustinFreemanu%
Steve HodgesSteveHodgest'
Jamie ShottonJamieShotton!s)
Pushmeet KohliPushmeetKohli*r3Richard A. NewcombeRichardA.Newcombe#q+
David MolyneauxDavidMolyneaux
\
)	<09>g\<00>-
!<02>7/1GGPushPull++<07>PushPull tools are implemented in most commercial 3D modeling suites. Their purpose is to intuitively transform a face, edge, or vertex, and then to adapt the polygonal mesh locally. However, previous approaches have limitations: Some allow adjustments only when adjacent faces are orthogonal; others support slanted surfaces but never create new details. Moreover, self-intersections and edge-collapses during editing are either ignored or work only partially for solid geometry. To overcome these limitations, we introduce the PushPull++ tool for rapid polygonal modeling. In our solution, we contribute novel methods for adaptive face insertion, adjacent face updates, edge collapse handling, and an intuitive user interface that automatically proposes useful drag directions. We show that PushPull++ reduces the complexity of common modeling tasks by up to an order of magnitude when compared with existing tools.ACM Trans. Graph.computer_graphics/2017-09-11T23:06:25.0919938962017-09-11T23:06:25.091993896<EFBFBD>>,
C<02>#
1GGInteractive Horizon Mapping<07>Shadows play an important role in perceiving the shape and texture of an object. While some previous interactive shadowing methods are appropriate for casting shadows on other geometry they can not be applied to bump maps (which contain no explicit geometry.) Horizon Mapping is a technique used to compute shadows for bump-mapped surfaces. We map the technique into modern graphics API's and extend it to account more accurately for the geometry of the underlying surface. We also use it to represent limited self-shadowing for pure geometry. In mapping the algorithm to hardware, we use a novel method to interpolate orientation in tangent space over the surface. We show results of self-shadowing at frame rates.computer_graphics/2017-09-11T23:06:24.7205668952017-09-11T23:06:24.720566895+	]

1GGLight Propagation Volumes in Cryengine 3<07>computer_graphics/2017-09-11T23:06:24.6665859382017-09-11T23:06:24.666585938<EFBFBD>T*
)<02>-I1GGThe Redox Code<07>SIGNIFICANCE
The redox code is a set of principles that defines the positioning of the nicotinamide adenine dinucleotide (NAD, NADP) and thiol/disulfide and other redox systems as well as the thiol redox proteome in space and time in biological systems. The code is richly elaborated in an oxygen-dependent life, where activation/deactivation cycles involving O₂ and H₂O₂ contribute to spatiotemporal organization for differentiation, development, and adaptation to the environment. Disruption of this organizational structure during oxidative stress represents a fundamental mechanism in system failure and disease.


RECENT ADVANCES
Methodology in assessing components of the redox code under physiological conditions has progressed, permitting insight into spatiotemporal organization and allowing for identification of redox partners in redox proteomics and redox metabolomics.


CRITICAL ISSUES
Complexity of redox networks and redox regulation is being revealed step by step, yet much still needs to be learned.


FUTURE DIRECTIONS
Detailed knowledge of the molecular patterns generated from the principles of the redox code under defined physiological or pathological conditions in cells and organs will contribute to understanding the redox component in health and disease. Ultimately, there will be a scientific basis to a modern redox medicine.Antioxidants & redox signalingcomputer_graphics/2017-09-11T23:06:24.6271999512017-09-11T23:06:24.627199951

M<0C><0B>	&
M<00>V1
w<02>1GGImaging vector fields using line integral convolution<07>Imaging vector fields has applications in science, art, image processing and special effects. An effective new approach is to use linear and curvilinear filtering techniques to locally blur textures along a vector field. This approach builds on several previous tex-It is, however, unique because it is local, one-dimensional and independent of any predefined geometry or texture. The technique is general and capable of imaging arbitrary two-and three-dimensional vector fields. The local one-dimensional nature of the algorithm lends itself to highly parallel and efficient implementations. Furthermore, the curvilinear filter is capable of rendering detail on very intricate vector fields. Combining this technique with other rendering and image processing techniques — like periodic motion filtering — results in richly informative and striking images. The technique can also produce novel special effects. 1. INTRODUCTION Upon first inspection, imaging vector fields appears to have limited application — confined primarily to scientific visualization. However, much of the form and shape in our environment is a function of not only image intensity and color, but also of directional information such as edges. Painters, sculptors, photographers , image processors[16] and computer graphics researchers[9] have recognized the importance of direction in the process of image creation and form. Hence, algorithms that can image such directional information have wide application across both scientific and artistic domains. Such algorithms should possess a number of desirable and sometimes conflicting properties including: accuracy, locality of calculation, simplicity, controllability and generality. Line Integral Convolution (LIC) is a new technique that possesses many of these properties. Its generality allows for the introduction of a comSIGGRAPHcomputer_graphics/2017-09-11T23:06:25.4613239752017-09-11T23:06:25.461323975<EFBFBD>H0
5<02>#/1GGInstant architecture<07>This paper presents a new method for the automatic modeling of architecture. Building designs are derived using split grammars, a new type of parametric set grammar based on the concept of shape. The paper also introduces an attribute matching system and a separate control grammar, which offer the flexibility required to model buildings using a large variety of different styles and design ideas. Through the adaptive nature of the design grammar used, the created building designs can either be generic or adhere closely to a specified goal, depending on the amount of data available.ACM Trans. Graph.computer_graphics/2017-09-11T23:06:25.3904060062017-09-11T23:06:25.390406006<EFBFBD>./
<00>
'1GGShape Grammars and the Generative Specification of Painting and Sculpture<07>IFIP Congresscomputer_graphics/2017-09-11T23:06:25.2005490722017-09-11T23:06:25.200549072<EFBFBD>[.
}<02>31CCDiminished reality for augmented reality interior design<07>A modular real-time diminished reality pipeline for indoor applications is presented. The pipeline includes a novel inpainting method which requires no prior information of the textures behind the object to be diminished. The inpainting method operates on rectified images and adapts to scene illumination. In typically challenging illumination situations, the method produces more realistic results in indoor scenes than previous approaches. Modularity enables using alternative implementations in different stages and adapting the pipeline for different applications. Finally, practical solutions to problems occurring in diminished reality applications, for example interior design, are discussed.The Visual Computercomputer_graphics/2017-09-11T23:06:25.16040212017-09-11T23:06:25.1604021

k<0C>f
k<00>x4
s<02>I/-GGHigh-quality single-shot capture of facial geometry<07>This paper describes a passive stereo system for capturing the 3D geometry of a face in a single-shot under standard light sources. The system is low-cost and easy to deploy. Results are submillimeter accurate and commensurate with those from state-of-the-art systems based on active lighting, and the models meet the quality requirements of a demanding domain like the movie industry. Recovered models are shown for captures from both high-end cameras in a studio setting and from a consumer binocular-stereo camera, demonstrating scalability across a spectrum of camera deployments, and showing the potential for 3D face modeling to move beyond the professional arena and into the emerging consumer market in stereoscopic photography.
 Our primary technical contribution is a modification of standard stereo refinement methods to capture pore-scale geometry, using a qualitative approach that produces visually realistic results. The second technical contribution is a calibration method suited to face capture systems. The systemic contribution includes multiple demonstrations of system robustness and quality. These include capture in a studio setup, capture off a consumer binocular-stereo camera, scanning of faces of varying gender and ethnicity and age, capture of highly-transient facial expression, and scanning a physical mask to provide ground-truth validation.ACM Trans. Graph.computer_vision/2017-09-11T23:06:25.7520791022017-09-11T23:06:25.752079102<EFBFBD>(3
}<02>/-GGCoupled 3D reconstruction of sparse facial hair and skin<07>Although facial hair plays an important role in individual expression, facial-hair reconstruction is not addressed by current face-capture systems. Our research addresses this limitation with an algorithm that treats hair and skin surface capture together in a coupled fashion so that a high-quality representation of hair fibers as well as the underlying skin surface can be reconstructed. We propose a passive, camera-based system that is robust against arbitrary motion since all data is acquired within the time period of a single exposure. Our reconstruction algorithm detects and traces hairs in the captured images and reconstructs them in 3D using a multiview stereo approach. Our coupled skin-reconstruction algorithm uses information about the detected hairs to deliver a skin surface that lies underneath all hairs irrespective of occlusions. In dense regions like eyebrows, we employ a hair-synthesis method to create hair fibers that plausibly match the image data. We demonstrate our scanning system on a number of individuals and show that it can successfully reconstruct a variety of facial-hair styles together with the underlying skin surface.ACM Trans. Graph.computer_vision/2017-09-11T23:06:25.6421398932017-09-11T23:06:25.642139893<EFBFBD>l2
M<02>S/1GGProcedural modeling of buildings<07><i>CGA shape</i>, a novel shape grammar for the procedural modeling of CG architecture, produces building shells with high visual quality and geometric detail. It produces extensive architectural models for computer games and movies, at low cost. Context sensitive shape rules allow the user to specify interactions between the entities of the hierarchical shape descriptions. Selected examples demonstrate solutions to previously unsolved modeling problems, especially to consistent mass modeling with volumetric shapes of arbitrary orientation. <i>CGA shape</i> is shown to efficiently generate massive urban models with unprecedented level of detail, with the virtual rebuilding of the archaeological site of Pompeii as a case in point.ACM Trans. Graph.computer_graphics/2017-09-11T23:06:25.5835639652017-09-11T23:06:25.583563965
<00>
<07><04><00><00>a8<00><02>+%GGFinding race conditions in Erlang with QuickCheck and PULSE<07>We address the problem of testing and debugging concurrent, distributed Erlang applications. In concurrent programs, race conditions are a common class of bugs and are very hard to find in practice. Traditional unit testing is normally unable to help finding all race conditions, because their occurrence depends so much on timing. Therefore, race conditions are often found during system testing, where due to the vast amount of code under test, it is often hard to diagnose the error resulting from race conditions. We present three tools (QuickCheck, PULSE, and a visualizer) that in combination can be used to test and debug concurrent programs in unit testing with a much better possibility of detecting race conditions. We evaluate our method on an industrial concurrent case study and illustrate how we find and analyze the race conditions.ICFPconcurrency/2017-09-11T23:06:26.3465319822017-09-11T23:06:26.346531982<EFBFBD>R7<00><02>y%GGHeap architectures for concurrent languages using message passing<07>We discuss alternative heap architectures for languages that rely on automatic memory management and implement concurrency through asynchronous message passing. We describe how interprocess communication and garbage collection happens in each architecture, and extensively discuss the tradeoffs that are involved. In an implementation setting (the Erlang/OTP system) where the rest of the runtime system is unchanged, we present a detailed experimental comparison between these architectures using both synthetic programs and large commercial products as benchmarks.MSP/ISMMconcurrency/2017-09-11T23:06:26.1239641112017-09-11T23:06:26.123964111<EFBFBD>}6<00>/<02>7%GGEverything you always wanted to know about synchronization but were afraid to ask<07>This paper presents the most exhaustive study of synchronization to date. We span multiple layers, from hardware cache-coherence protocols up to high-level concurrent software. We do so on different types of architectures, from single-socket -- uniform and non-uniform -- to multi-socket -- directory and broadcast-based -- many-cores. We draw a set of observations that, roughly speaking, imply that scalability of synchronization is mainly a property of the hardware.SOSPconcurrency/2017-09-11T23:06:25.9857990722017-09-11T23:06:25.985799072<EFBFBD>g5
s<02>'/-GGPanorama weaving: fast and flexible seam processing<07>A fundamental step in stitching several pictures to form a larger mosaic is the computation of boundary seams that minimize the visual artifacts in the transition between images. Current seam computation algorithms use optimization methods that may be slow, sequential, memory intensive, and prone to finding suboptimal solutions related to local minima of the chosen energy function. Moreover, even when these techniques perform well, their solution may not be perceptually ideal (or even good). Such an inflexible approach does not allow the possibility of user-based improvement. This paper introduces the <i>Panorama Weaving</i> technique for seam creation and editing in an image mosaic. First, <i>Panorama Weaving</i> provides a procedure to create boundaries for panoramas that is fast, has low memory requirements and is easy to parallelize. This technique often produces seams with lower energy than the competing global technique. Second, it provides the first interactive technique for the exploration of the seam solution space. This powerful editing capability allows the user to automatically extract energy minimizing seams given a sparse set of constraints. With a variety of empirical results, we show how <i>Panorama Weaving</i> allows the computation and editing of a wide range of digital panoramas including unstructured configurations.ACM Trans. Graph.computer_vision/2017-09-11T23:06:25.8137419432017-09-11T23:06:25.813741943
<02><0B><06><<02><00>A<
i<02>y#%GGExperience with Processes and Monitors in Mesa<07>The use of monitors for describing concurrency has been much discussed in the literature. When monitors are used in real systems of any size, however, a number of problems arise which have not been adequately dealt with: the semantics of nested monitor calls; the various ways of defining the meaning of WAIT; priority scheduling; handling of timeouts, aborts and other exceptional conditions; interactions with process creation and destruction; monitoring large numbers of small objects. These problems are addressed by the facilities described here for concurrent programming in Mesa. Experience with several substantial applications gives us some confidence in the validity of our solutions.Commun. ACMconcurrency/2017-09-11T23:06:26.8242260742017-09-11T23:06:26.824226074v;	
Q%GGHol<07>The Seventeen Provers of the Worldconcurrency/2017-09-11T23:06:26.6592819822017-09-11T23:06:26.659281982<EFBFBD>M:
_<02>+%GGMessage Analysis for Concurrent Languages<07>We describe an analysis-driven storage allocation scheme for concurrent languages that use message passing with copying semantics. The basic principle is that in such a language, data which is not part of any message does not need to be allocated in a shared data area. This allows for deallocation of thread-specific data without requiring global synchronization and often without even triggering garbage collection. On the other hand, data that is part of a message should preferably be allocated on a shared area, which allows for fast (O(1)) interprocess communication that does not require actual copying. In the context of a dynamically typed, higher-order, concurrent functional language, we present a static message analysis which guides the allocation. As shown by our performance evaluation, conducted using an industrial-strength language implementation , the analysis is effective enough to discover most data which is to be used as a message, and to allow the allocation scheme to combine the best performance characteristics of both a process-centric and a shared-heap memory architecture.SASconcurrency/2017-09-11T23:06:26.5853669432017-09-11T23:06:26.585366943<EFBFBD>y9
s<02>m%GGThe semantics of x86-CC multiprocessor machine code<07>Multiprocessors are now dominant, but real multiprocessors do not provide the sequentially consistent memory that is assumed by most work on semantics and verification. Instead, they have subtle relaxed (or weak) memory models, usually described only in ambiguous prose, leading to widespread confusion.
 We develop a rigorous and accurate semantics for x86 multiprocessor programs, from instruction decoding to relaxed memory model, mechanised in HOL. We test the semantics against actual processors and the vendor litmus-test examples, and give an equivalent abstract-machine characterisation of our axiomatic memory model. For programs that are (in some precise sense) data-race free, we prove in HOL that their behaviour is sequentially consistent. We also contrast the x86 model with some aspects of Power and ARM behaviour.
 This provides a solid intuition for low-level programming, and a sound foundation for future work on verification, static analysis, and compilation of low-level concurrent code.POPLconcurrency/2017-09-11T23:06:26.4369990232017-09-11T23:06:26.436999023
<02>
<EFBFBD>b<02><00>F?<00><02>S#'EEA Method for Obtaining Digital Signatures and Public-Key Cryptosystems<07>An encryption method is presented with the novel property that publicly revealing an encryption key does not thereby reveal the corresponding decryption key. This has two important consequences: (1) Couriers or other secure means are not needed to transmit keys, since a message can be enciphered using an encryption key publicly revealed by the intented recipient. Only he can decipher the message, since only he knows the corresponding decryption key. (2) A message can be &#8220;signed&#8221; using a privately held decryption key. Anyone can verify this signature using the corresponding publicly revealed encryption key. Signatures cannot be forged, and a signer cannot later deny the validity of his signature. This has obvious applications in &#8220;electronic mail&#8221; and &#8220;electronic funds transfer&#8221; systems. A message is encrypted by representing it as a number M, raising M to a publicly specified power e, and then taking the remainder when the result is divided by the publicly specified product, <italic>n</italic>, of two large secret primer numbers p and q. Decryption is similar; only a different, secret, power d is used, where e * d &#8801; 1(mod (p - 1) * (q - 1)). The security of the system rests in part on the difficulty of factoring the published divisor, <italic>n</italic>.Commun. ACMcryptography/2017-09-11T23:06:27.178482912017-09-11T23:06:27.17848291<EFBFBD>><00>
<02>#%GGTime, Clocks, and the Ordering of Events in a Distributed System<07>The concept of one event happening before another in a distributed system is examined, and is shown to define a partial ordering of the events. A distributed algorithm is given for synchronizing a system of logical clocks which can be used to totally order the events. The use of the total ordering is illustrated with a method for solving synchronization problems. The algorithm is then specialized for synchronizing physical clocks, and a bound is derived on how far out of synchrony the clocks can become.Commun. ACMconcurrency/2017-09-11T23:06:27.1089179692017-09-11T23:06:27.108917969<EFBFBD>~=
e<02>#GGMicroreboot - A Technique for Cheap Recovery<07>A significant fraction of software failures in large-scale Internet systems are cured by rebooting, even when the exact failure causes are unknown. However, rebooting can be expensive, causing nontrivial service disruption or downtime even when clusters and failover are employed. In this work we separate process recovery from data recovery to enable microrebooting – a fine-grain technique for surgically recovering faulty application components, without disturbing the rest of the application. We evaluate microrebooting in an Internet auction system running on an application server. Microreboots recover most of the same failures as full reboots, but do so an order of magnitude faster and result in an order of magnitude savings in lost work. This cheap form of recovery engenders a new approach to high availability: microreboots can be employed at the slightest hint of failure, prior to node failover in multi-node clusters, even when mistakes in failure detection are likely; failure and recovery can be masked from end users through transparent call-level re-tries; and systems can be rejuvenated by parts, without ever being shut down.OSDIcrash_only/2017-09-11T23:06:26.9153740232017-09-11T23:06:26.915374023

<01><00>
<01><0F><0F><0F><0F><0F><0F>dR?+<0E><0E><0E><0E><0E><0E><0E>yl[H4$
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
k
\
P
=
.

<0C><0C><0C><0C><0C><0C>nqcRA-<0B>#<0B><0B><0B><0B><02><0B><0B>oXC,	
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>?
<EFBFBD><02>
<01>
yQ
f
O
<
)

	<09>	<09>	<09>	<09>	<09>	<09>	s	^	I	6	#	
<08><08><08><08><08><08>zfO:$<02><07><07>
<01><07><07><07><07>{iXE5"<06><06><06><06><06><06><02><06>p`P:(<05><05><05><05><05><05><05>|oaSE4"
<04><02><04><04><04><04><04><04>pZG/<03><03><03><03><03><02><03><03><03><02><02>{dL6"

<01>
<01>
<01>
<01>
<01>+Anthony Liguori<05>
<01>1Amit Rahul Baishya<05><00>C. Borradori-Tolsa
<01>
C. Bocca<03>%C. Agostinho})C. A. R. Hoare<02>+Béla Bollobás<02>)Byung-Gon Chun<02>-By C. E. Shannon1Butler W. Larnpson/Butler W. Lampson<00>+
Bui Tuong Phongb#Bryan Par'Barmak Modrek#Binbin Chen<05>5Amir Hossein Gandomi<05>%Asim Shankar<05>!Ankur Taly<05>%Alex Monràs<05>+Albert Einstein<05>9Alejandro A. Schäffer<05>%Amihood Amir<05>;Andoni Lombide Carreton<05>'Adriaan Moors<05>'Boon Thau Loo<03>!Bob Sumner<00>
Bing Liu"

Bin ShengmBill Howe
!Bernd Kolb<02>%Bernd Bickel<00>%Bernard Wong
+Bernard MetzlerL/Benoît Garbinato\1Benjamin Schneider<05>'Benjamin Reed
/-Benjamin Hindman<03>5Benjamin H. Sigelmany-Benjamin C. Reed<03>#Ben Moseley`Ben Handy<00>'Bay-Wei Changr+Baruch Awerbuch<03>#Bart Samwel<00>)Barbara Liskov
e+Bapi ChatterjeeT%Balraj Singh
<01>#B. Öztürk<03>
B. ZhongB
B. Weber<04>
B. Veldt4B. Song<05>B. Sonk-B. Mohar Vitezic<03>1B. M. Santos Peixe\
B. KainzA#B. HolzmannB. Hansen-#B. GrahovacB. Foglia<03>B. Dreher<04>+B. ArrizabalagaP%B. Angermayrf-Avinash Lakshman7!Avi Kivity<05>!Avery Wang<02>1Austin T. ClementsW/Austin I. Eliazar<02>)
Ashley HartnerS+Ashish Motivala
<01>!Asaf Cidons-
Arvind NarayananB#
Arthur Guez+Arnar Birgisson<03>#Armando Fox<00>'Arjun Narayan<03>!Arjun Guha2'Arif Merchant
r%
Ariel Shamirh%Ariel Rabkin
8%Anupam Gupta<02>+Antony Rowstron<03>+Antony Courtneyz+Anton Kaplanyan<00>+Antoine Bossard<02>/Anthony D. Joseph
35Anne-Marie Kermarrec
<01>%Ann Wollrath
h-Anirban Dasgupta<05>+Animesh TrivediJ/Anil Madhavapeddy
<01>)Angus F. M. Ng!%Angelo Prado<02>1Angela Demke BrownF)Andy Konwinski
<)Andrey KhorlinO)Andrey Gubarev<00>+Andrew Warfield`+Andrew W. LeungV5
Andrew W. Fitzgibbonx'Andrew Turpin<02>'Andrew Tuckerb+Andrew P. Black
,+Andrew Mccallum)1Andrew Lookingbill<02>-Andrew Konwinski
5)Andrew Kennedy<02>/
Andrew J. Davisonw#Andrew Hume<02>)Andrew Handoko<02>%Andrew Fikes1%Andrej Bauer<02>-
Andrei Z. BroderN'Andreas Wöß<02>'Andreas Ulmer<00>/Andreas Haeberlen<03>'Andrea Bittau
w;Ana Candida Cruz Natali<02>#Amin Vahdat<02>?Ambrose Bonnaire-Sergeant1Alistair C. Veitch
t7Ali José Mashtizadeh
v!Ali Ghodsi<03>!Ali Dasdan
'Alfred Tarski<03>1
Alexandre KarpenkoW-
Alexandre Bartel/Alexander Thomson<00>3Alexander ReinefeldX+Alexander LloydS%Alex Pilchin8Alex Ho]!Alex Gyorif%Alex De Jong<02>%Alex Balikov
M-Alberto Dainotti<02>3Albert G. Greenberg
"
Alan Kay)Alan J. Demers
<01>#Alan Geller
^#Alan C. Kay<05>

Aja Huang5
Adrienne Porter Felt!Adi Shamir<00>'
Adam ChlipalaP;Achilleas L. D. Buisman<03>/Abraham Bernstein<03>)Abhishek Verma
E)Abhinandan Das
<01>)Aart J. C. Bik
l%A. YamaguchiOA. Yamadas'A. WinstanleybA. VazXA. Titova!+A. T. Abdelmoez<04>%A. SydorchukA. SuzukiA. Stepan<03>
A. Silva<04>+A. Shafigullina"%A. S. Hanafy<04>#A. Rizvanov)
A. Prete
!A. Popescu<03>!A. Pession!A. Peixoto<04>)A. P. Oliveira]'A. P. Kiyasov*#A. Oliveira
A. Morid!A. Martins<04>!A. Mansour<04>%
A. M. Turing%A. L. Simão<03>#A. Kourikou<04>%A. Koukofiki<04>'A. Galyavieva<05>-A. G. G. AntunesV#A. Floreani&%A. Ferlitschh)A. Facciorusso<04>'A. Eshraghian+%A. Colecchia<04>7A. Castiella EguzkizaH)A. Castanheira<04>
A. Alves[)A. Albuquerque<04>
A. AktasE)A. Abou Rached<04>+A. Abdulkhakova<05>)A. A. Gumerova'

<01><00>
<01>S?-<04><04><04><04><04><04><04>t]E/<03><03><03><03><03>
<01>
<01><0F><0F><0F><0F><0F><0F>o_K<.!<0E><0E><0E><0E><0E><0E><0E><0E>kZ@+
<0A>
<0A>
<0A>
<0A>
<0A>
<0A>
u
U
E
/

<0C><0C><0C><0C><0C>n
<01><0C>nW<02>=#<0B><0B><0B><0B><0B><0B>q]G4"
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>

o
b
V
G
7
'

	<09>	<09>	<09>	<09>	<09>	<09>	<09>	t	`	J	7	!	<08><08><08><08><08><08>*y_P<$<03><07><07><07><07><07><07><07>sbT<,
<06><06><06><06><06><06>s]F0Z<05><02><05><05><05>@<05><05>x<03>f
<02><02><02><02><02><02><02>tcP?*
<01>
<01>
<01>/Christian Limpach<05>#C. ErdoğduC. Choi<05>
Eric A. Brewer<03>#Eran Tromer<00>5Emmanuel Dellandréa,Emma Fulu<03>+Emin Gün Sirer
	+Emery D. Berger
W%
Eman RamadanA)
Elmar Eisemann_%
Elaine CohenU#Edwin Brady<02>-Edward J. Rykiel1Edsger W. Dijkstra<03>7Edmund B. Nightingale<!E. Zehnter<04>1Christopher J. Lee1Dawn Xiaodong Song<05>7Christopher M. Dawson<05>-Daniel S. Marcus<05>5Denise E. M. Penrose<05>)David W. Corne<05>+Christian Jacob<05>)David B. Fogel<05>)Dennis Ritchie<05>C. Bowlus"1C. Borradori-Tolsa
<01>
C. Bocca<03>%C. Agostinho})C. A. R. Hoare<02>+Béla Bollobás<02>)Byung-Gon Chun<02>-By C. E. Shannon1Butler W. Larnpson/Butler W. Lampson<00>+
Bui Tuong Phongb#Bryan Parno
<01>#
Bruce GoochV-
Brianna Satinoff?!Brian Zill
<01>#Brian Summa<00>%Brian M. Oki
<01>%Brian Hempel
+Brian F. Cooper]-
Brian D. Davisonz%Brian Cabral<00>)Brannon Batson<03>'Brandon WileyC'
Dennis ShashaM)Deniz Hastorun41Deniz Altınbükenq/Deniz Altinbüken<03>)
Demis Hassabis-1Deborah A. Wallach/'
Dean P. Jones-David W. Shipman
#David Ungarq%
David Silver-David S. Wishart:1
David S. Rosenblum-David S. Johnson
<01>+David R. Millen
<01>+David R. Karger
B#David Peleg<03>+David Patterson
='David P. Reedk/David Oppenheimer
H+
David Molyneauxq-David Menestrina

+David Mazières
y!David Lieb<02>1David Klaftenegger

David Kimo%
David JacobsX)David J. Scott
<01>'David J. Hand&#David Gregg<05>/David G. Andersen<00>)David F. Bacon
<01>+David D. Redell<00>)David D. Clarkl#David Chaum
<01>+
David A. Wagner1David A. Patterson
7)David A. Maltz
$Danny Digh5Daniel Winograd-Cort~'Daniel Sunday<02>%Daniel Pricea#Daniel Peng<03>1Daniel P. W. Ellis<02>%Daniel Mills
S3Daniel J. Bernstein<00>+Daniel J. Abadi<00>5Daniel H. H. Ingalls<05>-Daniel H. Greene
<01>'Daniel Genkin<00>-Daniel G. Bobrow<02>+
Daniel Cohen-Orj3Daniel C. Swinehart
<01>'Dan Steinberg'#Dan Ingalls!Dan Geiger%Dan Dumitriu
<01>Dan Dixon
<01>'
Damien Octeau	D. Stimac<03>!D. Shapiro0)D. SchmalstiegB!D. Orlandi<04>!D. Martins<04>D. Kovač<03>D. KimmD. Kang<05>!D. K. JangZ#D. Hartmann!D. H. Sinn<04>D. H. KohM
D. Gomes{D. G. Kim<05>
D. Festi'D. Branquinho!D. Bonazza<03>!D. Akiyamav+Cédric Fournet
'
Cyril Crassin\'Cynthia Dwork-Cristian Martín<03>)Craig ChamberspCory Hill<00>)Corinna Cortes/'Conor Mcbride<02>'Conal Elliott/Claude E. Shannon<03>-Chung-Chieh Shan;Christos T. Karamanolis
u?Christos H. Papadimitriou'5Christopher Strachey<02>5Christopher L. Reeve
/Christopher Clark<05>=Christine Van Vredendaal<00>-Christian Wimmer<02>+Christian Humer<02>+
Christian Fritz-Christian Franck<03>%Chris Thomas
<01>'Chris Okasaki)
Chris Jermaine5/
Chris J. Maddison-Chris Hawblitzel
<01>!Chris BondLAChitchanok Chuengsatiansup<00>-Chien-Chin HuangEChi Hon1Charalampos Rotsos
<01>%Chaoran YangRChao Yang
<01>'Changhoon Kim
<01>AChandra Shekhar Chandrakar-Chandan Shanbhag<03>%Chad Whipkey<00>+Carlos Maltzahn<00>5Carlos Delgado Kloos<03>#Carl Hewittd)Carl H. Hauser
<01>)
Carl A. Gunter-C.m.p. Rodrigues<03>#C. Τsoulas<04>
C. Yu7
C. Yaghi<04>
C. Xu6!C. Vincent,#C. Triantos<04>%C. Tiribelli<03>#C. TeixeiraWC. Tang<05>
C. SofiaC. Pavlov<04>)C. MeyenbergerG!C. Messina<04>!C. MartinsYC. Madl5C. M. Chackelevicius<03>!C. Lériasy3C. Ivascu-Siegfried<04>#C. Illiasch
C. Iancu<04>%C. Gregório
y
<EFBFBD>O<07>y<00>iC
9<02>c7'GGAcoustic Cryptanalysis<07>Many computers emit a high-pitched noise during operation, due to vibration in some of their electronic components. These acoustic emanations are more than a nuisance: They can convey information about the software running on the computer and, in particular, leak sensitive information about security-related computations. In a preliminary presentation (Eurocrypt’04 rump session), we have shown that different RSA keys induce different sound patterns, but it was not clear how to extract individual key bits. The main problem was the very low bandwidth of the acoustic side channel (under 20  kHz using common microphones, and a few hundred kHz using ultrasound microphones), and several orders of magnitude below the GHz-scale clock rates of the attacked computers. In this paper, we describe a new acoustic cryptanalysis key extraction attack, applicable to GnuPG’s implementation of RSA. The attack can extract full 4096-bit RSA decryption keys from laptop computers (of various models), within an hour, using the sound generated by the computer during the decryption of some chosen ciphertexts. We experimentally demonstrate such attacks, using a plain mobile phone placed next to the computer, or a more sensitive microphone placed 10 meters away.Journal of Cryptologycryptography/2017-09-11T23:06:27.4722089842017-09-11T23:06:27.472208984hB	3
#GGCrash-Only Software<07>HotOScrash_only/2017-09-11T23:06:27.3641020512017-09-11T23:06:27.364102051<EFBFBD>A
C<02>-I'GGAttacks on the WEP protocol<07>WEP is a protocol for securing wireless networks. In the past years, many attacks on WEP have been published, totally breaking WEP's security. This thesis summarizes all major attacks on WEP. Additionally a new attack, the PTW attack, is introduced, which was partially developed by the author of this document. Some advanced versions of the PTW attack which are more suiteable in certain environments are described as well. Currently, the PTW attack is fastest publicly known key recovery attack against WEP protected networks.IACR Cryptology ePrint Archivecryptography/2017-09-11T23:06:27.3485729982017-09-11T23:06:27.348572998<EFBFBD>@<00>/<02>[%GGSimple, Fast, and Practical Non-Blocking and Blocking Concurrent Queue Algorithms<07>Drawing ideas from previous authors, we present a new non-blocking concurrent queue algorithm and a new two-lock queue algorithm in which one enqueue and one de-queue can proceed concurrently. Both algorithms are simple , fast, and practical; we were surprised not to find them in the literature. Experiments on a 12-node SGI Challenge multiprocessor indicate that the new non-blocking queue consistently outperforms the best known alternatives; it is the clear algorithm of choice for machines that provide a universal atomic primitive (e.g. compare and swap or load linked/store conditional). The two-lock concurrent queue outperforms a single lock when several processes are competing simultaneously for access; it appears to be the algorithm of choice for busy queues on machines with non-universal atomic primitives (e.g. test and set). Since much of the motivation for non-blocking algorithms is rooted in their immunity to large, unpredictable delays in process execution, we report experimental results both for systems with dedicated processors and for systems with several processes multiprogrammed on each processor.PODCconcurrency/2017-09-11T23:06:27.3051669922017-09-11T23:06:27.305166992
0c0<00>0E
I<02>OI'GGNew directions in cryptography<07>Two kinds of contemporary developments in cryp-communications over an insecure channel order to use cryptog-tography are examined. Widening applications of teleprocess-raphy to insure privacy, however, it currently necessary for the ing have given rise to a need for new types of cryptographic communicating parties to share a key which is known to no systems, which minimize the need for secure key distribution one else. This is done by sending the key in advance over some channels and supply the equivalent of a written signature. This secure channel such a private courier or registered mail. A paper suggests ways to solve these currently open problems. private conversation between two people with no prior acquain-It also discusses how the theories of communication and compu-tance is a common occurrence in business, however, and it is tation are beginning to provide the tools to solve cryptographic unrealistic to expect initial business contacts to be postponed problems of long standing. long enough for keys to be transmitted by some physical means. The cost and delay imposed by this key distribution problem is a major barrier to the transfer of business communicationsIEEE Trans. Information Theorycryptography/2017-09-11T23:06:27.5887280272017-09-11T23:06:27.588728027<EFBFBD>D
_<02>
I'GGThe Moral Character of Cryptographic Work<07>Cryptography rearranges power: it configures who can do what, from what. This makes cryptography an inherently political tool, and it confers on the field an intrinsically moral dimension. The Snowden revelations motivate a reassessment of the political and moral positioning of cryptography. They lead one to ask if our inability to effectively address mass surveillance constitutes a failure of our field. I believe that it does. I call for a community-wide effort to develop more effective means to resist mass surveillance. I plead for a reinvention of our disciplinary culture to attend not only to puzzles and math, but, also, to the societal implications of our work. Preamble. Most academic cryptographers seem to think that our field is a fun, deep, and politically neutral game—a set of puzzles involving communicating parties and notional adversaries. This vision of who we are animates a field whose work is intellectually impressive and rapidly produced, but also quite inbred and divorced from real-world concerns. Is this what cryptography should be like? Is it how we should expend the bulk of our intellectual capital? For me, these questions came to a head with the Snowden disclosures of 2013. If cryptography's most basic aim is to enable secure communications, how could it not be a colossal failure of our field when ordinary people lack even a modicum of communication privacy when interacting electronically? Yet I soon realized that most cryptographers didn't see it this way. Most seemed to feel that the disclosures didn't even implicate us cryptographers. I think that they do. So I want to talk about the moral obligations of cryptographers , and my community as a whole. This is not a topic cryptographers routinely discuss. In this post-Snowden era, I think it needs to be. The essay and talk are addressed to the cryptographic community—my community— and the words " we " and " our " should be so interpreted. I apologize in advance if I offend anyone with any of my comments; nothing of the sort is my intent.IACR Cryptology ePrint Archivecryptography/2017-09-11T23:06:27.5243620612017-09-11T23:06:27.524362061

d	<09>	6H<00>)J
)<02>-GGCuckoo Hashing<07>We present a simple and efficient dictionary with worst case constant lookup time, equaling the theoretical performance of the classic dynamic perfect hashing scheme of Dietzfelbinger et al. The space usage is similar to that of binary search trees, i.e., three words per key on average. The practicality of the scheme is backed by extensive experiments and comparisons with known methods, showing it to be quite competitive also in the average case.ESAdata_structures/2017-09-11T23:06:28.2831799322017-09-11T23:06:28.283179932<EFBFBD>kI
Y<02>o
-EERRB-Trees: Efficient Immutable Vectors<07>Immutable vectors are a convenient data structure for functional programming and part of the standard library of modern languages like Clojure and Scala. The common implementation is based on wide trees with a fixed number of children per node, which allows fast indexed lookup and update operations. In this paper we extend the vector data type with a new underlying data structure, Relaxed Radix Balanced Trees (RRB-Trees), and show how this structure allows immutable vector concatenation, insert-at and splits in O(logN) time while maintaining the index, update and iteration speeds of the original vector data structure.data_structures/2017-09-11T23:06:28.082377932017-09-11T23:06:28.08237793<EFBFBD>+H	Kq/GGImmutability Changes Everything<07>We need it, we can afford it, and the time is now.CIDRdata_replication/2017-09-11T23:06:27.9392070312017-09-11T23:06:27.939207031~G	e

'GGMathematical Aspects of Consciousness Theory<07>cryptography/2017-09-11T23:06:27.7440400392017-09-11T23:06:27.744040039<EFBFBD>F
!<02>II'GGNTRU Prime<07>Focus of this talk: motivation. 2 Can we predict future attacks? 1996 Dobbertin–Bosselaers– Preneel " RIPEMD-160: a strengthened version of RIPEMD " : " It is anticipated that these techniques can be used to produce collisions for MD5 and perhaps also for RIPEMD. This will probably require an additional effort, but it no longer seems as far away as it was a year ago. " 1996 Robshaw: Collisions " should be expected " ; upgrade " when practical and convenient ". 1 rime. Bernstein y of Illinois at Chicago & he Universiteit Eindhoven o/papers.html ime is joint work with: ok Chuengsatiansup nge van Vredendaal he Universiteit Eindhoven this talk: motivation. 2 Can we predict future attacks? 1996 Dobbertin–Bosselaers– Preneel " RIPEMD-160: a strengthened version of RIPEMD " : " It is anticipated that these techniques can be used to produce collisions for MD5 and perhaps also for RIPEMD. This will probably require an additional effort, but it no longer seems as far away as it was a year ago. " 1996 Robshaw: Collisions " should be expected " ; upgrade " when practical and convenient ". Imagine " This is The atta not brea MD5, so point of speculati is contro and crea state of alternati the very 1 is at Chicago & iteit Eindhoven .html t work with: gsatiansup endaal iteit Eindhoven motivation.IACR Cryptology ePrint Archivecryptography/2017-09-11T23:06:27.6524519042017-09-11T23:06:27.652451904
<00>;<00><0F>r6
<0E><0E>G 
<0A>
<0A>
z
7<0C><0C><0C>b<0B><0B>A
<EFBFBD>
<EFBFBD>
z
B	<09>	<09>	<09>	<09>	G	<08><08><00><08>@<07><07>PG,<06><06>s/<05><05>q<04><04>V<03><03>`%<02><02><02>C
<01>
<01>
<01>
L
<00><00><00>%MA survey on reactive programming
<01>
Blue native PAGE.)Bitcoin
4/Bimodal Multicast<00>@<04>
Bigtable: A Distributed Storage System for Structured Data
$a<04>CBeehive: O(1) Lookup Performance for Power-Law Query Distributions in Peer-to-Peer Overlays
:!EBayesian Network Classifiers
9Backtracking iterators<00>V<04>-Back to the future: the story of Squeak, a practical Smalltalk written in itself
,]
BIG Cache6oASAP: the Alternative Splicing Annotation Project
<01>-]Axiomatic Basis for Computer Programming
7qAutomatic prediction of emotions induced by movies<00>7qAuthoritative Sources in a Hyperlinked Environment<00>:wAuctions and bidding: A guide for computer scientists<00>C
Attacks on the WEP protocolA:wAsynchronous functional reactive programming for GUIs<00>P<04>#
Architectural Styles and the Design of Network-based Software Architectures	I<04>Applications of Machine Learning in Cancer Prediction and Prognosis<00>d<04>IAnd then there were none: a stall-free real-time garbage collector for reconfigurable hardware<00>8u
Analyzing inter-application communication in Android|<04>{
Analysis of Three Bayesian Network Inference Algorithms: Variable Elimination, Likelihood Weighting, and Gibbs Sampling/aAn introduction to argumentation semantics<00>5o
An improved illumination model for shaded display W<04>/An implementation and semantics for transactional memory introspection in Haskell
nC<04>An elementary proof of a theorem of Johnson and Lindenstrauss
2gAn Industrial Strength Audio Search Algorithm
/aAn Analysis of the Cryptocurrency Industry
3U<04>+Adaptive Road Following using Self-Supervised Learning and Reverse Optical Flow<00>9
Acoustic CryptanalysisC8u
Above the Clouds: A Berkeley View of Cloud Computingfc<04>GASAP: Automatic Smoothing for Attention Prioritization in Streaming Time Series Visualization
/aA wait-free queue as fast as fetch-and-add<00>+YA unified theory of garbage collection<00>G<04>A theoretician's guide to the experimental analysis of algorithms<00>7qA taxonomy of suffix array construction algorithms

'QA survey of network virtualization
<01>._A sparse Johnson: Lindenstrauss transform
u/c
A simple totally ordered broadcast protocoleA<04>
A program optimization for automatic database result caching+YA mathematical theory of communication
o0cA history of Haskell: being lazy with class<00>3A history of Erlang<00>B<04>A file undelete with Aho-Corasick algorithm in file recovery<00>7qA few useful things to know about machine learning<00>M<04>A comparison of software and hardware techniques for x86 virtualization

/A Wait-Free Stack
ya<04>CA Versatile Scheme for Routing Highly Variable Traffic in Service Overlays and IP Backbones
9E<04>A Universal Modular ACTOR Formalism for Artificial Intelligence
7X<04>1A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition<00>"I
A Theory of Inferred Causation^<04>=A Response to Cheriton and Skeen's Criticism of Causal and Totally Ordered Communication
6#IA Poor Man's Concurrency Monad
m#K
A Note on Distributed Computingr@<04>
A New Approach to Linear Filtering and Prediction Problems1PK<04>
A Method for Obtaining Digital Signatures and Public-Key Cryptosystems?B<04>A LISP garbage-collector for virtual-memory computer systems<00>=}A Hundred Impossibility Proofs for Distributed Computing
89uA History of the Virtual Synchrony Replication Model
5-]A Gossip-Style Failure Detection Service<00>&OA Fast String Searching Algorithm
<{A Fast Quantum Mechanical Algorithm for Database Search<00>`<04>AA Data-driven Method for the Detection of Close Submitters in Online Learning Environments
j'S
A DNA-Based Archival Storage System(SA Calculus of Communicating Systems<00>;yA Byzantine Fault Tolerant Distributed Commit Protocol
=<}
3-Sweep: extracting editable objects from a single photo$P<04>#
2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm
<04>B<00>?<07><07>v52<06>n<03><06><03>n"<02><0F><0F>ol<05>"<06>
!<0E><0E><0E>Y
<0A>
<0A>
j
6<0C><0C>
<01>v1<0B><0B>w"
<EFBFBD>
<EFBFBD>(
:
	<00>	<09>	<09><05>	<09><00><00>	5	<08><08>
^m<05>
<01><04><04><00>I<04>F<04>%MDeprecating the Observer Pattern
<01>'QDesign Principles Behind Smalltalk
r8sDavis's Poetic Dialogue with Leiris's Autobiography
q<{Comments on a problem in concurrent programming control
c(SDining Cryptographers are Practical
^M<04>Distributed Snapshots: Determining Global States of Distributed Systems
FZ<04>5Consistent Global States of Distributed Systems: Fundamental Concepts and Mechanisms
E<04>Bitcoin
4,]
BIG Cache Abstraction for Cache NetworksG<04>Chain Replication for Supporting High Throughput and Availability
Bm<04>[Can Programming Be Liberated From the von Neumann Style? A Functional Style and its Algebra of Programs<00>K<04>
Calvin: fast distributed transactions for partitioned database systemsNL<04>
CRUSH: controlled, scalable, decentralized placement of replicated dataS CByzantine Chain Replication
<@<04>
Building global and scalable systems with atomic multicast
-P<04>!Breadth-first numbering: lessons from a small exercise in algorithm design<00>&OBreach: Reviving the Crime Attack<00>
"
Everything you always wanted to know about synchronization but were afraid to ask6-Event-Driven FRP<00>4m
Evaluating Generative Models for Text Generation=Epidemic Broadcast Trees<00><{Epidemic Algorithms for Replicated Database Maintenance<00>*WEnd-To-End Arguments in System De7Chaotic bat algorithm
<01>*WDefending against network IDS evasion
<01>*WDistributed Authorization in Vanadium
<01>c<04>GDai-depur: an Integrated Supervisory Multi-level Architecture for Wastewater Treatment Plants
<01>7Buridan’s Principle
<01>F<04>
Cognitive Computing: A Brief Survey and Open Research Challenges
<01>5Bouvier's Conjecture
;/
Blue native PAGE.)/Bimodal Multicast<00>@<04>
Bigtable: A Distributed Storage System for Structured Data
$a<04>CBeehive: O(1) Lookup Performance for Power-Law Query Distributions in Peer-to-Peer Overlays
:!EBayesian Network Classifiers
9Backtracking iterators<00>V<04>-Back to the future: the story of Squeak, a practical Smalltalk written in itself
C
Direct and Indirect Effects<}
Diminished reality for augmented reality interior design.P<04>#
Digital Video Stabilization and Rolling Shutter Correction using Gyroscopes5Differential Privacy<00>K<04>Design requirements for technologies that encourage physical activity<00>;yDefining gamification: a service marketing perspective<00>/
Deep Colorization%5mDecoding speech in the presence of other sources<00>0cDatabase metatheory: asking the big queries
"F<04>
Dapper, a Large-Scale Distributed Systems Tracing Infrastructure
Aa<04>CDP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks<00>+YD-Expressions: Lisp Power, Dylan Style<00>)
Cuckoo HashingJT<04>)Crossing the gap from imperative to functional programming through refactoring<00>3
Crash-Only SoftwareB<}
Coupled 3D reconstruction of sparse facial hair and skin38sCounting Large Numbers of Events in Small Registers
+YCoq: the world's best macro assembler?<00>D<04>	Copysets: Reducing the Frequency of Data Loss in Cloud Storage
@)W
Continuous Shading of Curved Surfaces!A<04>
Consistency in Non-Transactional Distributed Storage SystemsQS<04>'Consistency and fault tolerance for erasure-coded distributed storage systems
,3iConsensus in the presence of partial synchrony
?_<04>?Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data<00>(U
Computing Machinery and Intelligence*WCompressors with Vanes-Based Diffuser
:wComposable and compilable macros: : you want it when?<00>6oCompiling pattern matching to good decision trees<00>,[Communication Theory of Secrecy Systems
'QCommunicating Sequential Processes<00><{Commodifying Replicated State Machines with OpenReplica
>L<04>
Chord: A scalable peer-to-peer lookup service for internet applicationsh*Y
Causal Diagrams for Empirical Research;{
Cassandra – A Decentralized Structured Storage SystemV)UCan SPDY really make the web faster?<00>

<01><00>
<01><0F><0F><0F><0F><0F><0F><0F>tk[Q<02>H?2<0E><0E><0E><0E><0E>N<0E><0E><0E>w_PG8"/

<0A>
<0A>
<0A>
<01>
<0A>
<0A>
<0A>
<0A>D
<0A>
r
i
Z
O
=
<0C><0C><0C><0C><0C><0C><0C><0C><0C>}h]P:1	<0B><0B><0B><0B><0B><0B><0B>ylbdXG;1<02>(
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
<EFBFBD>
w
j
a
U
I
@
4
$

	<09><02>	<09>	<09>	<09>	<09>	<09>	<09>	{%	i	^	R	:	,			<08><08><08><08><08><08><08><08><08>}j_rTH<1&p	<07><07><07><02><07><07><07><07><07><03><07>{h<02>Q<2#
<06><06><06><06><06><06>wj\K7!<05><02><05><05><05><05><02><05>yhX@$?<02><04><04>W<04><04><04>o`P>-<03> 
<03><03><03>6L<03><03><03><03>