| 2019 | A Tighter Analysis of Randomised Policy Iteration. | Meet Taraviya, Shivaram Kalyanakrishnan |
| 2019 | Exact Sampling of Directed Acyclic Graphs from Modular Distributions. | Topi Talvitie, Aleksis Vuoksenmaa, Mikko Koivisto |
| 2019 | Variational Inference of Penalized Regression with Submodular Functions. | Koh Takeuchi, Yuichi Yoshida, Yoshinobu Kawahara |
| 2019 | Co-training for Policy Learning. | Jialin Song, Ravi Lanka, Yisong Yue, Masahiro Ono |
| 2019 | Sliced Score Matching: A Scalable Approach to Density and Score Estimation. | Yang Song, Sahaj Garg, Jiaxin Shi, Stefano Ermon |
| 2019 | A Sparse Representation-Based Approach to Linear Regression with Partially Shuffled Labels. | Martin Slawski, Mostafa Rahmani, Ping Li |
| 2019 | Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks. | Qi She, Anqi Wu |
| 2019 | Intervening on Network Ties. | Eli Sherman, Ilya Shpitser |
| 2019 | Approximate Relative Value Learning for Average-reward Continuous State MDPs. | Hiteshi Sharma, Mehdi Jafarnia-Jahromi, Rahul Jain |
| 2019 | Evacuate or Not? A POMDP Model of the Decision Making of Individuals in Hurricane Evacuation Zones. | Adithya Raam Sankar, Prashant Doshi, Adam Goodie |
| 2019 | Stability of Linear Structural Equation Models of Causal Inference. | Karthik Abinav Sankararaman, Anand Louis, Navin Goyal |
| 2019 | On the Relationship Between Satisfiability and Markov Decision Processes. | Ricardo Salmon, Pascal Poupart |
| 2019 | Be Greedy: How Chromatic Number meets Regret Minimization in Graph Bandits. | Aadirupa Saha, Shreyas Sheshadri, Chiranjib Bhattacharyya |
| 2019 | Efficient Planning Under Uncertainty with Incremental Refinement. | Juan Carlos Saboro, Joachim Hertzberg |
| 2019 | On First-Order Bounds, Variance and Gap-Dependent Bounds for Adversarial Bandits. | Roman Pogodin, Tor Lattimore |
| 2019 | Exclusivity Graph Approach to Instrumental Inequalities. | Davide Poderini, Rafael Chaves, Iris Agresti, Gonzalo Carvacho, Fabio Sciarrino |
| 2019 | Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. | Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani |
| 2019 | Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions. | Tim Pearce, Russell Tsuchida, Mohamed Zaki, Alexandra Brintrup, Andy Neely |
| 2019 | Sinkhorn AutoEncoders. | Giorgio Patrini, Rianne van den Berg, Patrick Forr, Marcello Carioni, Samarth Bhargav, Max Welling, Tim Genewein, Frank Nielsen |
| 2019 | A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations. | Biswajit Paria, Kirthevasan Kandasamy, Barnabs Pczos |
| 2019 | The Role of Memory in Stochastic Optimization. | Antonio Orvieto, Jonas Kohler, Aurlien Lucchi |
| 2019 | Variational Regret Bounds for Reinforcement Learning. | Ronald Ortner, Pratik Gajane, Peter Auer |
| 2019 | Towards a Better Understanding and Regularization of GAN Training Dynamics. | Weili Nie, Ankit Patel |
| 2019 | CCMI : Classifier based Conditional Mutual Information Estimation. | Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan |
| 2019 | Causal Discovery with General Non-Linear Relationships using Non-Linear ICA. | Ricardo Pio Monti, Kun Zhang, Aapo Hyvrinen |