| 2020 | 99% of Worker-Master Communication in Distributed Optimization Is Not Needed. | Konstantin Mishchenko, Filip Hanzely, Peter Richtrik |
| 2020 | Measurement Dependence Inducing Latent Causal Models. | Alex Markham, Moritz Grosse-Wentrup |
| 2020 | High Dimensional Discrete Integration over the Hypergrid. | Raj Kumar Maity, Arya Mazumdar, Soumyabrata Pal |
| 2020 | Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation. | Alexander Lyzhov, Yuliya Molchanova, Arsenii Ashukha, Dmitry Molchanov, Dmitry P. Vetrov |
| 2020 | Regret Analysis of Bandit Problems with Causal Background Knowledge. | Yangyi Lu, Amirhossein Meisami, Ambuj Tewari, William Yan |
| 2020 | Sensor Placement for Spatial Gaussian Processes with Integral Observations. | Krista Longi, Chang Rajani, Tom Sillanp, Joni Mkinen, Timo Rauhala, Ari Salmi, Edward Hggstrm, Arto Klami |
| 2020 | Exploration Analysis in Finite-Horizon Turn-based Stochastic Games. | Jialian Li, Yichi Zhou, Tongzheng Ren, Jun Zhu |
| 2020 | How Private Are Commonly-Used Voting Rules? | Ao Liu, Yun Lu, Lirong Xia, Vassilis Zikas |
| 2020 | Bounded Rationality in Las Vegas: Probabilistic Finite Automata Play Multi-Armed Bandits. | Xinming Liu, Joseph Y. Halpern |
| 2020 | Collapsible IDA: Collapsing Parental Sets for Locally Estimating Possible Causal Effects. | Yue Liu, Zhuangyan Fang, Yangbo He, Zhi Geng |
| 2020 | Efficient Rollout Strategies for Bayesian Optimization. | Eric Hans Lee, David Eriksson, David Bindel, Bolong Cheng, Mike Mccourt |
| 2020 | Complex Markov Logic Networks: Expressivity and Liftability. | Ondrej Kuzelka |
| 2020 | Semi-supervised learning, causality, and the conditional cluster assumption. | Julius von Kgelgen, Alexander Mey, Marco Loog, Bernhard Schlkopf |
| 2020 | Finite-Memory Near-Optimal Learning for Markov Decision Processes with Long-Run Average Reward. | Jan Kretnsk, Fabian Michel, Lukas Michel, Guillermo A. Prez |
| 2020 | Randomized Exploration for Non-Stationary Stochastic Linear Bandits. | Baekjin Kim, Ambuj Tewari |
| 2020 | Verifying Individual Fairness in Machine Learning Models. | Philips George John, Deepak Vijaykeerthy, Diptikalyan Saha |
| 2020 | Testing Goodness of Fit of Conditional Density Models with Kernels. | Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schlkopf |
| 2020 | Learning LWF Chain Graphs: A Markov Blanket Discovery Approach. | Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi |
| 2020 | Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation. | Marko Jrvenp, Aki Vehtari, Pekka Marttinen |
| 2020 | Deep Sigma Point Processes. | Martin Jankowiak, Geoff Pleiss, Jacob R. Gardner |
| 2020 | Spectral Methods for Ranking with Scarce Data. | Lalit Jain, Anna C. Gilbert, Umang Varma |
| 2020 | Locally Masked Convolution for Autoregressive Models. | Ajay Jain, Pieter Abbeel, Deepak Pathak |
| 2020 | Automated Dependence Plots. | David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar |
| 2020 | Multitask Soft Option Learning. | Maximilian Igl, Andrew Gambardella, Jinke He, Nantas Nardelli, N. Siddharth, Wendelin Boehmer, Shimon Whiteson |
| 2020 | Estimation Rates for Sparse Linear Cyclic Causal Models. | Jan-Christian Htter, Philippe Rigollet |