3rd Offline RL Workshop: Offline RL as a "Launchpad"

Neural Information Processing Systems (NeurIPS)

December 2, 2022

@OfflineRL · #OFFLINERL

The paper pdf can be accessed by clicking on the title of the paper. For incorrect links / fixes, please create a pull request at https://github.com/offline-rl-neurips/2022/ .

Oral Presentations (PDF) Authors Video
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, {*Vikash Kmar, *Amy Zhang}
Efficient Planning in a Compact Latent Action Space Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian Video
Choreographer: Learning and Adapting Skills in Imagination Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar Video
Pareto-Efficient Decision Agents for Offline Multi-Objective Reinforcement Learning Baiting Zhu, Meihua Dang, Aditya Grover Video



Poster Presentations (PDF) Authors Video
Benchmarking Offline Reinforcement Learning Algorithms for E-Commerce Order Fraud Evaluation Soysal Degirmenci, Chris Jones
Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction Brahma S. Pavse, Josiah P. Hanna Video
Towards Data-Driven Offline Simulations of Online Reinforcement Learning Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra, Alex Lamb, John Langford, Paul Mineiro, Sebastian Kochman
Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based RL David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, Jake Varley Video
Using Confounded Data in Offline RL Maxime Gasse, Damien Grasset, Guillaume Gaudron, Pierre-Yves Oudeyer Video
Offline evaluation in RL: soft stability weighting to combine fitted Q-learning and model-based methods Briton Park, Angela Zhou, Bin Yu, Carrie Wu Video
A Connection between One-Step Regularization and Critic Regularization in Reinforcement Learning Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov Video
Imitation from Observation With Bootstrapped Contrastive Learning Medric B. Djeafea Sonwa, Johanna Hansen, Eugene Belilovsky
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation Dan Qiao, Yu-Xiang Wang Video
Offline Robot Reinforcement Learning with Uncertainty-Guided Human Expert Sampling Ashish Kumar, Ilya Kuzovkin Video
Uncertainty-Driven Pessimistic Q-Ensemble for Offline-to-Online Reinforcement Learning Ingook Jang, Seonghyun Kim Video
Mutual Information Regularized Offline Reinforcement Learning Xiao Ma, Bingyi Kang, Zhongwen Xu, Min Lin, Shuicheng YAN Video
Control Graph as Unified IO for Morphology-Task Generalization Hiroki Furuta, Yusuke Iwasawa, Yutaka Matsuo, Shixiang Shane Gu Video
Optimal Transport for Offline Imitation Learning Yicheng Luo, Zhengyao Jiang, Samuel Cohen, Edward Grefenstette, Marc Peter Deisenroth Video
Towards User-Interactive Offline Reinforcement Learning Phillip Swazinna, Steffen Udluft, Thomas Runkler Video
Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size Alexander Nikulin, Vladislav Kurenkov, Denis Tarasov, Dmitry Akimov, Sergey Kolesnikov Video
CORL: Research-oriented Deep Offline Reinforcement Learning Library Denis Tarasov, Alexander Nikulin, Dmitry Akimov, Vladislav Kurenkov, Sergey Kolesnikov Video
Hybrid RL: Using Both Offline and Online Data can Make RL Efficient Yuda Song*, Yifei Zhou*, Ayush Sekhari, J. Andrew Bagenll, Akshay Krishnamurthy, Wen Sun Video
Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Hatch, Aryan Jain, Tianhe Yu,Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta Video
Matrix Estimation for Offline Evaluation in Reinforcement Learning with Low-Rank Structure Xumei Xi, Christina Lee Yu, Yudong Chen Video
Let Offline RL Flow: Training Conservative Agents in the Latent Space of Normalizing Flows Dmitry Akimov, Vladislav Kurenkov, Alexander Nikulin, Denis Tarasov, Sergey Kolesnikov Video
Offline Reinforcement Learning on Real Robot with Realistic Data Sources Gaoyue Zhou, Liyiming Ke, Siddhartha Srinivasa, Abhinav Gupta, Aravind Rajeswaran, Vikash Kumar Video
Dynamics-Augmented Decision Transformer for Offline Dynamics Generalization Changyeon Kim, Junsu Kim, Younggyo Seo, Kimin Lee, Honglak Lee, Jinwoo Shin Video
ABC: Adversarial Behavioral Cloning for Offline Mode-Seeking Imitation Learning Eddy Hudson, Ishan Durugkar, Garrett Warnell, Peter Stone Video
Trajectory-based Explainability Framework for Offline RL Shripad Deshmukh, Arpan Dasgupta, Chirag Agarwal, Nan Jiang, Balaji Krishnamurthy, Georgios Theocharous, Jayakumar Subramanian Video
Can Active Sampling Reduce Causal Confusion in Offline RL? Gunshi Gupta, Tim G. J. Rudner, Rowan Thomas McAllister, Adrien Gaidon, Yarin Gal Video
Bayesian Q-learning with Imperfect Expert Demonstrations Fengdi Che, Xiru Zhu, Doina Precup, David Meger, Gregory Dudek Video
SPRINT: Scalable Semantic Policy Pre-training via Language Instruction Relabeling Jesse Zhang, Karl Pertsch, Jiahui Zhang, Taewook Nam, Sung Ju Hwang, Xiang Ren, Joseph J. Lim Video
Raisin: Residual Algorithms for Versatile Offline Reinforcement Learning Braham Snyder, Yuke Zhu Video
Residual Model-Based Reinforcement Learning for Physical Dynamics Zakariae EL ASRI, Clément RAMBOUR, Nicolas THOME, Vincent Le Guen Video
Offline Policy Comparison with Confidence: Benchmarks and Baselines Anurag Koul,Mariano Phielipp, Alan Fern Video
Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies Shiva Kanth Sujit, Pedro Braga, Jorg Bornschein, Samira Ebrahimi Kahou Video
Offline Policy Evaluation for Reinforcment Learning with Adaptively Collected Data Sunil Madhow, Dan Qiao, Ming Yin, Yu-Xiang Wang Video
Contrastive Example-Based Control Kyle Hatch, Sarthak J Shetty, Benjamin Eysenbach, Tianhe Yu, Rafael Rafailov, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn Video
Offline Reinforcement Learning with Closed-Form Policy Improvement Operators Jiachen Li, Edwin Zhang, Ming Yin, Qinxun Bai, Yu-Xiang Wang, William Yang Wang Video
Boosting Offline Reinforcement Learning via Data Rebalancing Yang Yue, Bingyi Kang, Xiao Ma, Zhongwen Xu, Gao Huang, Shuicheng Yan Video
Revisiting Bellman Errors for Offline Model Selection Joshua P. Zitovsky, Daniel de Marchi, Rishabh Agarwal, Michael R. Kosorok Video
Guiding Offline Reinforcement Learning Using Safety Expert Richa Verma, Kartik Bharadwaj, Harshad Khadilkar, Balaraman Ravindran Video
Improving TD3-BC: Relaxed Policy Constraint for Offline Reinforcement Learning and Stable Online Fine-Tuning Alex Beeson, Giovanni Montana Video
Model-based Trajectory Stitching for Improved Offline Reinforcement Learning Charles A. Hepburn, Giovanni Montana Video
Domain Generalization for Robust Model-Based Offline Reinforcement Learning Alan Clark, Shoaib Ahmed Siddiqui, Robert Kirk, Usman Anwar, Stephen Chung, David Krueger Video
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin, Pablo Samuel Castro, Marc G. Bellemare
Does Zero-Shot Reinforcement Learning Exist ? Ahmed Touati, Jérémy Rapin, Yann Ollivier
On- and Offline Multi-agent Reinforcement Learning for Disease Mitigation using Human Mobility Data Sofia Hurtado, Radu Marculescu