Papers
Efficient and Consistent Adversarial Bipartite Matching
Rizal Fathony, Sima Behpour, Xinhua Zhang et al.
More Robust Doubly Robust Off-policy Evaluation
Mehrdad Farajtabar, Yinlam Chow, Mohammad Ghavamzadeh
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
Stefan Falkner, Aaron Klein, Frank Hutter
The Limits of Maxing, Ranking, and Preference Learning
Moein Falahatgar, Ayush Jain, Alon Orlitsky et al.
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF)
Trefor Evans, Prasanth Nair
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
Lasse Espeholt, Hubert Soyer, Remi Munos et al.
Parallel and Streaming Algorithms for K-Core Decomposition
Hossein Esfandiari, Silvio Lattanzi, Vahab Mirrokni
Beyond the One-Step Greedy Approach in Reinforcement Learning
Yonathan Efroni, Gal Dalal, Bruno Scherrer et al.
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
Gintare Karolina Dziugaite, Daniel Roy
Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn’s Algorithm
Pavel Dvurechensky, Alexander Gasnikov, Alexey Kroshnin
A Distributed Second-Order Algorithm You Can Trust
Celestine Duenner, Aurelien Lucchi, Matilde Gargiani et al.
Investigating Human Priors for Playing Video Games
Rachit Dubey, Pulkit Agrawal, Deepak Pathak et al.
Gradient Descent Learns One-hidden-layer CNN: Don’t be Afraid of Spurious Local Minima
Simon Du, Jason Lee, Yuandong Tian et al.
Essentially No Barriers in Neural Network Energy Landscape
Felix Draxler, Kambis Veschgini, Manfred Salmhofer et al.
Randomized Block Cubic Newton Method
Nikita Doikov, Peter Richtarik, University Edinburgh
Probabilistic Recurrent State-Space Models
Andreas Doerr, Christian Daniel, Martin Schiegg et al.
Coordinated Exploration in Concurrent Reinforcement Learning
Maria Dimakopoulou, Benjamin Van Roy
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning
Thomas Dietterich, George Trimponias, Zhitang Chen
Noisin: Unbiased Regularization for Recurrent Neural Networks
Adji Bousso Dieng, Rajesh Ranganath, Jaan Altosaar et al.
Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski p-Norms
Charlie Dickens, Graham Cormode, David Woodruff
Learning to Act in Decentralized Partially Observable MDPs
Jilles Dibangoye, Olivier Buffet
Alternating Randomized Block Coordinate Descent
Jelena Diakonikolas, Lorenzo Orecchia