2nd Offline Reinforcement Learning Workshop

Neural Information Processing Systems (NeurIPS)

December 14, 2021

@OfflineRL · #OFFLINERL

The paper pdf can be accessed by clicking on the title of the paper.

Oral Presentations (PDF) Authors Video
What Matters in Learning from Offline Human Demonstrations for Robot Manipulation Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, Roberto Martín-Martín Video
PulseRL: Enabling Offline Reinforcement Learning for Digital Marketing Systems via Conservative Q-Learning Luckeciano Melo*, Luana Martins*, Bryan Oliveira*, Bruno Brandao*, Douglas Soares, Telma Lima Video
What Would the Expert do()?: Causal Imitation Learning Gokul Swamy, Sanjiban Choudhury, Drew Bagnell, Steven Wu Video
Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation Dylan Foster, Akshay Krishnamurthy, David Simchi-Levi, Yunzong Xu



Poster Presentations (PDF) Authors Video
DCUR: Data Curriculum for Teaching via Samples with Reinforcement Learning Daniel Seita, Abhinav Gopal, Zhao Mandi, John Canny
TiKick: Towards Playing Multi-agent Football Full Games from Single-agent Demonstrations Shiyu Huang, Wenze Chen, Longfei Zhang, Shizhen Xu, Ziyang Li, Fengming Zhu, Deheng Ye, Ting Chen, Jun Zhu Video
d3rlpy: An Offline Deep Reinforcement Learning Library Takuma Seno, Michita Imai Video
Latent Geodesics of Model Dynamics for Offline Reinforcement Learning Guy Tennenholtz, Nir Baram, Shie Mannor Video
Domain Knowledge Guided Offline Q Learning Xiaoxuan Zhang, Sijia Zhang, Yen-Yun Yu
Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning Kajetan Schweighofer, Markus Hofmarcher, Marius-Constantin Dinu, Philipp Renz, Angela Bitto-Nemling, Vihang Patil, Sepp Hochreiter Video
Unsupervised Learning of Temporal Abstractions using Slot-based Transformers Anand Gopalakrishnan, Kazuki Irie, Juergen Schmidhuber, Sjoerd van Steenkiste
Counter-Strike Deathmatch with Large-Scale Behavioural Cloning Tim Pearce, Jun Zhu Video
Modern Hopfield Networks for Sample-Efficient Return Decomposition from Demonstrations Michael Widrich, Markus Hofmarcher, Vihang Patil, Angela Bitto-Nemling, Sepp Hochreiter Video
Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage Masatsohii Uehara, Wen Sun Video
Importance of Representation Learning for Off-Policy Fitted Q-Evaluation Xian Wu, Nevena Lazic, Dong Yin, Cosmin Paduraru Video
Offline Contextual Bandits for Wireless Network Optimization Miguel Suau, Alexandros Agapitos, David Lynch, Derek Farrell, Mingqi Zhou, and Aleksandar Milenovic Video
Robust On-Policy Data Collection for Data-Efficient Policy Evaluation Rujie Zhong, Josiah P. Hanna, Lukas Schäfer, Stefano V. Albrecht Video
Doubly Pessimistic Algorithms for Strictly Safe Off-Policy Optimization Sanae Amani, Lin F. Yang Video
Offline RL With Resource Constrained Online Deployment Jayanth Reddy Regatti, Aniket Anand Deshmukh, Frank Cheng, Young Hun Jung, Abhishek Gupta, Urun Dogan Video
Personalization for Web-based Services using Offline Reinforcement Learning Pavlos A. Apostolopoulos, Zehui Wang, Hanson Wang, Chad Zhou, Kittipat Virochsiri, Norm Zhou, Igor L. Markov
Offline Reinforcement Learning with Implicit Q-Learning Ilya Kostrikov, Ashvin Nair, Sergey Levine
Pessimistic Model Selection for Offline Deep Reinforcement Learning Chao-Han Huck Yang*, Zhengling Qi*, Yifang Cui, Pin-Yu Chen Video
BATS: Best Action Trajectory Stitching Ian Char*, Viraj Mehta*, Adam Villaflor, John M. Dolan, Jeff Schneider
Single-Shot Pruning for Offline Reinforcement Learning Samin Yeasar Arnob, Riyasat Ohib, Sergey Plis, Doina Precup
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization Thanh Nguyen-Tang, Sunil Gupta, A.Tuan Nguyen, Svetha Venkatesh
Improving Zero-shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions Bogdan Mazoure, Ilya Kostrikov, Ofir Nachum, Jonathan Tompson Video
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning Yi Zhao, Rinu Boney, Alexander Ilin, Juho Kannala, Joni Pajarinen Video
Quantile Filtered Imitation Learning David Brandfonbrener, William Whitney, Rajesh Ranganath, Joan Bruna Video
Benchmarking Sample Selection Strategies for Batch Reinforcement Learning Yuwei Fu, Di Wu, Benoit Boulet Video
Dynamic Mirror Descent based Model Predictive Control for Accelerating Robot Learning Utkarsh A. Mishra*, Soumya R. Samineni*, Prakhar Goel, Chandravaran Kunjeti, Himanshu Lodha, Aman Singh, Aditya Sagi, Shalabh Bhatnagar, Shishir Kolathaya Video
MBAIL: Multi-Batch Best Action Imitation Learning utilizing Sample Transfer and Policy Distillation Di Wu, Tianyu Li, David Meger, Michael Jenkin, Xue Liu, Gregory Dudek
Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget Matters Vladislav Kurenkov, Sergey Kolesnikov Video
Offline Reinforcement Learning with Munchausen Regularization Hsin-Yu Liu, Balaji Bharathan, Rajesh Gupta, Dezhi Hong Video
Importance of Empirical Sample Complexity Analysis for Offline Reinforcement Learning Samin Yeasar Arnob, Riashat Islam, Doina Precup
Discrete Uncertainty Quantification Approach for Offline RL Javier Corrochano, Javier García, Rubén Majadas, Cristina Ibanez-Llano, Sergio Pérez, Fernando Fernández Video
Pretraining For Language-Conditioned Imitation with Transformers Aaron (Louie) Putterman, Kevin Lu, Igor Mordatch, Pieter Abbeel
Stateful Offline Contextual Policy Evaluation and Learning Nathan Kallus, Angela Zhou
Learning Value Functions from Undirected State-only Experience Matthew Chang*, Arjun Gupta*, Saurabh Gupta Video
Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations Haoran Xu, Xianyuan Zhan, Honglei Yin, Huiling Qin Video
Model-Based Offline Planning with Trajectory Pruning Xianyuan Zhan, Xiangyu Zhu, Haoran Xu Video
TRAIL: Near-Optimal Imitation Learning with Suboptimal Data Sherry Yang, Sergey Levine, Ofir Nachum
Offline Meta-Reinforcement Learning for Industrial Insertion Tony Z. Zhao*, Jianlan Luo*, Oleg Sushkov, Rugile Pevceviciute, Nicolas Heess, Jon Scholz, Stefan Schaal, Sergey Levine Video
Sim-to-Real Interactive Recommendation via Off-Dynamics Reinforcement Learning Junda Wu, Zhuihui Xie, Tong Yu, Qizhi Li, Shuai Li
Why so pessimistic? Estimating uncertainties for offline rl through ensembles, and why their independence matters Seyed Kamyar Seyed Ghasemipour, Shixiang (Shane) Gu, Ofir Nachum Video
Example-Based Offline Reinforcement Learning without Rewards Kyle Hatch*, Tianhe Yu*, Rafael Rafailov, Chelsea Finn
The Reflective Explorer: Online Meta-Exploration from Offline Data in Realistic Robotic Tasks Rafael Rafailov, Varun Kumar, Tianhe Yu, Avi Singh, Mariano Phielipp, Chelsea Finn