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Offline Reinforcement Learning at Multiple Frequencies


Jul 26, 2022
Kaylee Burns, Tianhe Yu, Chelsea Finn, Karol Hausman

* Project website: https://sites.google.com/stanford.edu/adaptive-nstep-returns/ 

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Latent-Variable Advantage-Weighted Policy Optimization for Offline RL


Mar 16, 2022
Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Yuan Gao, Jianhao Wang, Wenzhe Li, Bin Liang, Chelsea Finn, Chongjie Zhang


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How to Leverage Unlabeled Data in Offline Reinforcement Learning


Feb 03, 2022
Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Chelsea Finn, Sergey Levine


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Conservative Data Sharing for Multi-Task Offline Reinforcement Learning


Sep 16, 2021
Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn


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Efficiently Identifying Task Groupings for Multi-Task Learning


Sep 10, 2021
Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn


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Visual Adversarial Imitation Learning using Variational Models


Jul 16, 2021
Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn


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COMBO: Conservative Offline Model-Based Policy Optimization


Feb 16, 2021
Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn


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Offline Reinforcement Learning from Images with Latent Space Models


Dec 21, 2020
Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn


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Variable-Shot Adaptation for Online Meta-Learning


Dec 14, 2020
Tianhe Yu, Xinyang Geng, Chelsea Finn, Sergey Levine

* First two authors contribute equally 

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Measuring and Harnessing Transference in Multi-Task Learning


Oct 29, 2020
Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn


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