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Poster
Mon 17:00 What are the Statistical Limits of Offline RL with Linear Function Approximation?
Ruosong Wang, Dean Foster, Sham M Kakade
Poster
Tue 1:00 Risk-Averse Offline Reinforcement Learning
Núria Armengol Urpí, Sebastian Curi, Andreas Krause
Poster
Tue 9:00 Text Generation by Learning from Demonstrations
Richard Pang, He He
Poster
Tue 17:00 The Importance of Pessimism in Fixed-Dataset Policy Optimization
Jacob Buckman, Carles Gelada, Marc G Bellemare
Poster
Tue 17:00 Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization
Michael Zhang, Tom Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, ziyu wang, Mohammad Norouzi
Poster
Wed 9:00 OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning
Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum
Poster
Wed 9:00 DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs
aayam shrestha, Stefan Lee, Prasad Tadepalli, Alan Fern
Poster
Thu 1:00 Representation Balancing Offline Model-based Reinforcement Learning
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
Spotlight
Thu 12:30 DeepAveragers: Offline Reinforcement Learning By Solving Derived Non-Parametric MDPs
aayam shrestha, Stefan Lee, Prasad Tadepalli, Alan Fern
Spotlight
Thu 19:35 What are the Statistical Limits of Offline RL with Linear Function Approximation?
Ruosong Wang, Dean Foster, Sham M Kakade
Workshop
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
Workshop
COMBO: Conservative Offline Model-Based Policy Optimization
Tianhe (Kevin) Yu, Aviral Kumar, Aravind Rajeswaran, Rafael Rafailov, Sergey Levine, Chelsea Finn