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J. Andrew Bagnell

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Hybrid Inverse Reinforcement Learning

Feb 13, 2024
Juntao Ren, Gokul Swamy, Zhiwei Steven Wu, J. Andrew Bagnell, Sanjiban Choudhury

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The Virtues of Pessimism in Inverse Reinforcement Learning

Feb 08, 2024
David Wu, Gokul Swamy, J. Andrew Bagnell, Zhiwei Steven Wu, Sanjiban Choudhury

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Inverse Reinforcement Learning without Reinforcement Learning

Mar 26, 2023
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu

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The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms

Mar 01, 2023
Anirudh Vemula, Yuda Song, Aarti Singh, J. Andrew Bagnell, Sanjiban Choudhury

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Hybrid RL: Using Both Offline and Online Data Can Make RL Efficient

Oct 13, 2022
Yuda Song, Yifei Zhou, Ayush Sekhari, J. Andrew Bagnell, Akshay Krishnamurthy, Wen Sun

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Game-Theoretic Algorithms for Conditional Moment Matching

Aug 19, 2022
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu

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Sequence Model Imitation Learning with Unobserved Contexts

Aug 03, 2022
Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu

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Minimax Optimal Online Imitation Learning via Replay Estimation

Jun 02, 2022
Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu, Jiantao Jiao, Kannan Ramchandran

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