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Efficient Planning in a Compact Latent Action Space


Aug 25, 2022
Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian

* Code available at https://github.com/ZhengyaoJiang/latentplan 

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Spectral Decomposition Representation for Reinforcement Learning


Aug 19, 2022
Tongzheng Ren, Tianjun Zhang, Lisa Lee, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai

* The first two authors contribute equally 

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Making Linear MDPs Practical via Contrastive Representation Learning


Jul 14, 2022
Tianjun Zhang, Tongzheng Ren, Mengjiao Yang, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai

* ICML 2022. The first two authors contribute equally 

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Contrastive Learning as Goal-Conditioned Reinforcement Learning


Jun 15, 2022
Benjamin Eysenbach, Tianjun Zhang, Ruslan Salakhutdinov, Sergey Levine

* Code is available on the website: https://ben-eysenbach.github.io/contrastive_rl 

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Graph Backup: Data Efficient Backup Exploiting Markovian Transitions


May 31, 2022
Zhengyao Jiang, Tianjun Zhang, Robert Kirk, Tim Rocktäschel, Edward Grefenstette


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A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning


Nov 22, 2021
Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai

* The first two authors contribute equally 

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C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks


Oct 22, 2021
Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez


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Multi-objective Optimization by Learning Space Partitions


Oct 10, 2021
Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian


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Learning Space Partitions for Path Planning


Jul 14, 2021
Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian


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