| 2020 | Conditional Importance Sampling for Off-Policy Learning. | Mark Rowland, Anna Harutyunyan, Hado van Hasselt, Diana Borsa, Tom Schaul, Rmi Munos, Will Dabney |
| 2020 | Adaptive Trade-Offs in Off-Policy Learning. | Mark Rowland, Will Dabney, Rmi Munos |
| 2020 | Optimal Approximation of Doubly Stochastic Matrices. | Nikitas Rontsis, Paul Goulart |
| 2020 | Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information. | Esther Rolf, Michael I. Jordan, Benjamin Recht |
| 2020 | Beyond exploding and vanishing gradients: analysing RNN training using attractors and smoothness. | Antnio H. Ribeiro, Koen Tiels, Luis Antonio Aguirre, Thomas B. Schn |
| 2020 | Prediction Focused Topic Models via Feature Selection. | Jason Ren, Russell Kunes, Finale Doshi-Velez |
| 2020 | FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization. | Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani, Ali Jadbabaie, Ramtin Pedarsani |
| 2020 | Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions. | Giorgia Ramponi, Amarildo Likmeta, Alberto Maria Metelli, Andrea Tirinzoni, Marcello Restelli |
| 2020 | Tensorized Random Projections. | Beheshteh T. Rakhshan, Guillaume Rabusseau |
| 2020 | Importance Sampling via Local Sensitivity. | Anant Raj, Cameron Musco, Lester Mackey |
| 2020 | Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions. | Kamiar Rahnama Rad, Wenda Zhou, Arian Maleki |
| 2020 | How fine can fine-tuning be? Learning efficient language models. | Evani Radiya-Dixit, Xin Wang |
| 2020 | A PTAS for the Bayesian Thresholding Bandit Problem. | Yue Qin, Jian Peng, Yuan Zhou |
| 2020 | Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes. | Zhaozhi Qian, Ahmed M. Alaa, Alexis Bellot, Mihaela van der Schaar, Jem Rashbass |
| 2020 | A Robust Univariate Mean Estimator is All You Need. | Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar |
| 2020 | Adversarial Robustness of Flow-Based Generative Models. | Phillip Pope, Yogesh Balaji, Soheil Feizi |
| 2020 | A principled approach for generating adversarial images under non-smooth dissimilarity metrics. | Aram-Alexandre Pooladian, Chris Finlay, Tim Hoheisel, Adam M. Oberman |
| 2020 | Deterministic Decoding for Discrete Data in Variational Autoencoders. | Daniil Polykovskiy, Dmitry P. Vetrov |
| 2020 | Sparse Hilbert-Schmidt Independence Criterion Regression. | Benjamin Poignard, Makoto Yamada |
| 2020 | A Deep Generative Model for Fragment-Based Molecule Generation. | Marco Podda, Davide Bacciu, Alessio Micheli |
| 2020 | Hamiltonian Monte Carlo Swindles. | Dan Piponi, Matthew D. Hoffman, Pavel Sountsov |
| 2020 | Statistical Estimation of the Poincar constant and Application to Sampling Multimodal Distributions. | Loucas Pillaud-Vivien, Francis R. Bach, Tony Lelivre, Alessandro Rudi, Gabriel Stoltz |
| 2020 | A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning. | Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk, Quoc Tran-Dinh |
| 2020 | Stable behaviour of infinitely wide deep neural networks. | Stefano Peluchetti, Stefano Favaro, Sandra Fortini |
| 2020 | Infinitely deep neural networks as diffusion processes. | Stefano Peluchetti, Stefano Favaro |