From b08e9c0e8222d539bc9b2c2a5ba46072533d3b6b Mon Sep 17 00:00:00 2001 From: David Rio Deiros Date: Mon, 1 May 2017 11:27:54 -0400 Subject: [PATCH] Add entry for asap. --- time_series/README.md | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/time_series/README.md b/time_series/README.md index 44e8cfd..bdf4515 100644 --- a/time_series/README.md +++ b/time_series/README.md @@ -17,7 +17,14 @@ The included documents are: and suitable for stochastic processes. This makes them attractive for processing high-frequency data in finance and other fields. Using a basic set of operators, we easily construct more powerful combined - operators which cover a wide set of typical applications. - + operators which cover a wide set of typical applications. +* [:scroll:](https://github.com/papers-we-love/papers-we-love/blob/master/time_series/ts-asap.pdf) + [ASAP: Automatic Smoothing for Attention Prioritization in Streaming Time Series Visualization](http://futuredata.stanford.edu/asap/) - Kexin Rong, Peter Bailis + Time Series smoothing method to better prioritize attention in time series + exploration and monitoring visualizations, smooth the time series as much as + possible to remove noise while still retaining large-scale structure. We + develop a new technique for automatically smoothing streaming time series + that adaptively optimizes this trade-off between noise reduction (i.e., + variance) and outlier retention (i.e., kurtosis).