| Year | Title | Authors |
|---|---|---|
| 2018 | Delayed Impact of Fair Machine Learning | Lydia T. Liu, University of California Berkeley Sarah Dean, University of California Berkeley Esther Rolf, University of California Berkeley Max Simchowitz, University of California Berkeley Moritz Hardt, University of California Berkeley |
| 2018 | Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples | Anish Athalye, Massachusetts Institute of Technology Nicholas Carlini, University of California Berkeley David Wagner, University of California Berkeley |
| 2017 | Understanding Black-box Predictions via Influence Functions | Pang Wei Koh & Percy Liang, Stanford University |
| 2016 | Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling | Christopher De Sa, Stanford University Chris Re, Stanford University Kunle Olukotun, Stanford University Pixel Recurrent Neural Networks Aaron Van den Oord, Google Nal Kalchbrenner, Google Koray Kavukcuoglu, Google |
| 2016 | Dueling Network Architectures for Deep Reinforcement Learning | Ziyu Wang, Google Tom Schaul, Google Matteo Hessel, Google Hado van Hasselt, Google Marc Lanctot, Google Nando de Freitas, University of Oxford |
| 2015 | A Nearly-Linear Time Framework for Graph-Structured Sparsity | Chinmay Hegde, Massachusetts Institute of Technology Piotr Indyk, Massachusetts Institute of Technology Ludwig Schmid, Massachusetts Institute of Technology |
| 2015 | Optimal and Adaptive Algorithms for Online Boosting | Alina Beygelzimer, Yahoo! Research Satyen Kale, Yahoo! Research Haipeng Luo, Princeton University |
| 2014 | Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis | Jian Tang, Peking University Zhaoshi Meng, University of Michigan XuanLong Nguyen, University of Michigan Qiaozhu Mei, University of Michigan Ming Zhang, Peking University |
| 2013 | Vanishing Component Analysis | Roi Livni, The Hebrew University of Jerusalum David Lehavi, Hewlett-Packard Labs Sagi Schein, Hewlett-Packard Labs Hila Nachlieli, Hewlett-Packard Labs Shai Shalev Shwartz, The Hebrew University of Jerusalum Amir Globerson, The Hebrew University of Jerusalum |
| 2013 | Fast Semidifferential-based Submodular Function Optimization | Rishabh Iyer, University of Washington Stefanie Jegelka, University of California Berkeley Jeff Bilmes, University of Washington |
| 2012 | Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring | Sungjin Ahn, University of California Irvine Anoop Korattikara, University of California Irvine Max Welling, University of California Irvine |
| 2011 | Computational Rationalization: The Inverse Equilibrium Problem | Kevin Waugh, Carnegie Mellon University Brian Ziebart, Carnegie Mellon University Drew Bagnell, Carnegie Mellon University |
| 2010 | Hilbert Space Embeddings of Hidden Markov Models | Le Song, Carnegie Mellon University Byron Boots, Carnegie Mellon University Sajid M. Siddiqi, Google Geoffrey Gordon, Carnegie Mellon University Alex Smola, Yahoo! Research |
| 2009 | Structure preserving embedding | Blake Shaw & Tony Jebara, Columbia University |
| 2008 | SVM Optimization: Inverse Dependence on Training Set Size | Shai Shalev-Shwartz & Nathan Srebro, Toyota Technological Institute at Chicago |
| 2007 | Information-theoretic metric learning | Jason V. Davis, University of Texas at Austin Brian Kulis, University of Texas at Austin Prateek Jain, University of Texas at Austin Suvrit Sra, University of Texas at Austin Inderjit S. Dhillon, University of Texas at Austin |
| 2006 | Trading convexity for scalability | Ronan Collobert, NEC Labs America Fabian Sinz, NEC Labs America Jason Weston, NEC Labs America Léon Bottou, NEC Labs America |
| 2005 | A support vector method for multivariate performance measures | Thorsten Joachims, Cornell University |
| 1999 | Least-Squares Temporal Difference Learning | Justin A. Boyan, NASA Ames Research Center |
