Papers
Learning the Structure of Generative Models without Labeled Data
Stephen H. Bach, Bryan He, Alexander Ratner et al.
Minimax Regret Bounds for Reinforcement Learning
Mohammad Gheshlaghi Azar, Ian Osband, Rémi Munos
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
Haim Avron, Michael Kapralov, Cameron Musco et al.
An Alternative Softmax Operator for Reinforcement Learning
Kavosh Asadi, Michael L. Littman
A Closer Look at Memorization in Deep Networks
Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas et al.
Generalization and Equilibrium in Generative Adversarial Nets (GANs)
Sanjeev Arora, Rong Ge, Yingyu Liang et al.
Wasserstein Generative Adversarial Networks
Martin Arjovsky, Soumith Chintala, Léon Bottou
Oracle Complexity of Second-Order Methods for Finite-Sum Problems
Yossi Arjevani, Ohad Shamir
Deep Voice: Real-time Neural Text-to-Speech
Sercan Ö. Arık, Mike Chrzanowski, Adam Coates et al.
A Simple Multi-Class Boosting Framework with Theoretical Guarantees and Empirical Proficiency
Ron Appel, Pietro Perona
Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning
Oron Anschel, Nir Baram, Nahum Shimkin
Modular Multitask Reinforcement Learning with Policy Sketches
Jacob Andreas, Dan Klein, Sergey Levine
An Efficient, Sparsity-Preserving, Online Algorithm for Low-Rank Approximation
David Anderson, Ming Gu
Input Convex Neural Networks
Brandon Amos, Lei Xu, J. Zico Kolter
OptNet: Differentiable Optimization as a Layer in Neural Networks
Brandon Amos, J. Zico Kolter
Near-Optimal Design of Experiments via Regret Minimization
Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh et al.
Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU
Zeyuan Allen-Zhu, Yuanzhi Li
Faster Principal Component Regression and Stable Matrix Chebyshev Approximation
Zeyuan Allen-Zhu, Yuanzhi Li
Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition
Zeyuan Allen-Zhu, Yuanzhi Li
Learning Continuous Semantic Representations of Symbolic Expressions
Miltiadis Allamanis, Pankajan Chanthirasegaran, Pushmeet Kohli et al.
A Semismooth Newton Method for Fast, Generic Convex Programming
Alnur Ali, Eric Wong, J. Zico Kolter
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis
Ahmed M. Alaa, Scott Hu, Mihaela Schaar
Connected Subgraph Detection with Mirror Descent on SDPs
Cem Aksoylar, Lorenzo Orecchia, Venkatesh Saligrama
Local Bayesian Optimization of Motor Skills
Riad Akrour, Dmitry Sorokin, Jan Peters et al.