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Adding the trusting classifiers paper from the Seattle papers we love (#466)
chapter, presented on July 2017.
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* [Applications of Machine Learning to Location Data](http://www.berkkapicioglu.com/wp-content/uploads/2013/11/thesis_final.pdf) - Using machine learning to design and analyze novel algorithms that leverage location data.
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* ["Why Should I Trust You?" Explaining the Predictions of Any Classifier](http://www.kdd.org/kdd2016/papers/files/rfp0573-ribeiroA.pdf) - This paper introduces an explanation technique for any classifier in a interpretable manner.
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## Hosted Papers
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* :scroll: **[A Sparse Johnson-Lindenstrauss Transform](dimensionality_reduction/a-sparse-johnson-lindenstrauss-transform.pdf)**
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