Papers
A Reduction from Reinforcement Learning to No-Regret Online Learning
Ching-An Cheng, Remi Tachet Combes, Byron Boots et al.
A Robust Univariate Mean Estimator is All You Need
Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar
A Rule for Gradient Estimator Selection, with an Application to Variational Inference
Tomas Geffner, Justin Domke
ASAP: Architecture Search, Anneal and Prune
Asaf Noy, Niv Nayman, Tal Ridnik et al.
A Simple Approach for Non-stationary Linear Bandits
Peng Zhao, Lijun Zhang, Yuan Jiang et al.
A single algorithm for both restless and rested rotting bandits
Julien Seznec, Pierre Menard, Alessandro Lazaric et al.
Assessing Local Generalization Capability in Deep Models
Huan Wang, Nitish Shirish Keskar, Caiming Xiong et al.
A Stein Goodness-of-fit Test for Directional Distributions
Wenkai Xu, Takeru Matsuda
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning
Ming Yin, Yu-Xiang Wang
Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra Algorithms
Ping Ma, Xinlian Zhang, Xin Xing et al.
Asynchronous Gibbs Sampling
Alexander Terenin, Daniel Simpson, David Draper
A Theoretical and Practical Framework for Regression and Classification from Truncated Samples
Andrew Ilyas, Emmanouil Zampetakis, Constantinos Daskalakis
A Theoretical Case Study of Structured Variational Inference for Community Detection
Mingzhang Yin, Y. X. Rachel Wang, Purnamrita Sarkar
A Three Sample Hypothesis Test for Evaluating Generative Models
Casey Meehan, Kamalika Chaudhuri, Sanjoy Dasgupta
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games
Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien et al.
A Topology Layer for Machine Learning
Rickard Brüel Gabrielsson, Bradley J. Nelson, Anjan Dwaraknath et al.
Auditing ML Models for Individual Bias and Unfairness
Songkai Xue, Mikhail Yurochkin, Yuekai Sun
A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach
Aryan Mokhtari, Asuman Ozdaglar, Sarath Pattathil
A Unified Statistically Efficient Estimation Framework for Unnormalized Models
Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi et al.
A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments
Adam Foster, Martin Jankowiak, Matthew O’Meara et al.
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent
Eduard Gorbunov, Filip Hanzely, Peter Richtarik
Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models
Theo Galy-Fajou, Florian Wenzel, Manfred Opper
Automatic Differentiation of Sketched Regression
Hang Liao, Barak A. Pearlmutter, Vamsi K. Potluru et al.
Automatic Differentiation of Some First-Order Methods in Parametric Optimization
Sheheryar Mehmood, Peter Ochs