NIPS 2016 Proceedings
Advances in Neural Information Processing Systems 29 (NIPS 2016) The papers below appear in Advances in Neural Information Processing Systems 29 edited by D.D. Lee and M. Sugiyama and U.V. Luxburg and I. Guyon and R. Garnett. They are proceedings from the conference, "Neural Information Processing Systems 2016." Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much Bryan
Hidden Technical Debt in Machine Learning Systems
Hidden Technical Debt in Machine Learning Systems D. Sculley, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips {dsculley,gholt,dgg,edavydov,toddphillips}@google.com Google, Inc. Dietmar Ebner, Vinay Chaudhary, Michael Young, Jean-François Crespo, Dan Dennison {ebner,vchaudhary,mwyoung,jfcrespo,dennison}@google.com Google, Inc. Abstract Machine learning offers a fantastically powerful tool
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Examples are not enough, learn to criticize! Criticism for Interpretability
Understanding Dropout
