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PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration

Jul 15, 2021
Yuda Song, Wen Sun

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Pessimistic Model-based Offline RL: PAC Bounds and Posterior Sampling under Partial Coverage

Jul 13, 2021
Masatoshi Uehara, Wen Sun

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Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great Coverage

Jun 14, 2021
Jonathan D. Chang, Masatoshi Uehara, Dhruv Sreenivas, Rahul Kidambi, Wen Sun

* 42 pages, 5 figures, 7 tables 

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Corruption-Robust Offline Reinforcement Learning

Jun 11, 2021
Xuezhou Zhang, Yiding Chen, Jerry Zhu, Wen Sun

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Bilinear Classes: A Structural Framework for Provable Generalization in RL

Mar 19, 2021
Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang

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Fairness of Exposure in Stochastic Bandits

Mar 03, 2021
Lequn Wang, Yiwei Bai, Wen Sun, Thorsten Joachims

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Optimism is All You Need: Model-Based Imitation Learning From Observation Alone

Feb 22, 2021
Rahul Kidambi, Jonathan Chang, Wen Sun

* 25 pages, 3 figures, 1 tabular column 

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Robust Policy Gradient against Strong Data Corruption

Feb 16, 2021
Xuezhou Zhang, Yiding Chen, Xiaojin Zhu, Wen Sun

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Finite Sample Analysis of Minimax Offline Reinforcement Learning: Completeness, Fast Rates and First-Order Efficiency

Feb 05, 2021
Masatoshi Uehara, Masaaki Imaizumi, Nan Jiang, Nathan Kallus, Wen Sun, Tengyang Xie

* Under Review 

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Adaptive Federated Learning and Digital Twin for Industrial Internet of Things

Nov 01, 2020
Wen Sun, Shiyu Lei, Lu Wang, Zhiqiang Liu, Yan Zhang

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Learning the Linear Quadratic Regulator from Nonlinear Observations

Oct 08, 2020
Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford

* To appear at NeurIPS 2020 

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PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning

Aug 13, 2020
Alekh Agarwal, Mikael Henaff, Sham Kakade, Wen Sun

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Information Theoretic Regret Bounds for Online Nonlinear Control

Jun 22, 2020
Sham Kakade, Akshay Krishnamurthy, Kendall Lowrey, Motoya Ohnishi, Wen Sun

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FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs

Jun 18, 2020
Alekh Agarwal, Sham Kakade, Akshay Krishnamurthy, Wen Sun

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Provably Efficient Model-based Policy Adaptation

Jun 14, 2020
Yuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao

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Constrained episodic reinforcement learning in concave-convex and knapsack settings

Jun 09, 2020
Kianté Brantley, Miroslav Dudik, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun

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Arbitrary Style Transfer via Multi-Adaptation Network

May 27, 2020
Yingying Deng, Fan Tang, Weiming Dong, Wen Sun, Feiyue Huang, Changsheng Xu

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Exploration in Action Space

Mar 31, 2020
Anirudh Vemula, Wen Sun, J. Andrew Bagnell

* Presented at RSS 2018 in Learning and Inference in Robotics: Integrating Structure, Priors and Models workshop. arXiv admin note: text overlap with arXiv:1901.11503 

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Corruption Robust Exploration in Episodic Reinforcement Learning

Nov 20, 2019
Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins, Wen Sun

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Policy Poisoning in Batch Reinforcement Learning and Control

Oct 31, 2019
Yuzhe Ma, Xuezhou Zhang, Wen Sun, Xiaojin Zhu

* NeurIPS 2019 

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Optimal Sketching for Kronecker Product Regression and Low Rank Approximation

Sep 29, 2019
Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff

* A preliminary version of this paper appeared in NeurIPS 2019 

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Provably Efficient Imitation Learning from Observation Alone

Jun 11, 2019
Wen Sun, Anirudh Vemula, Byron Boots, J. Andrew Bagnell

* ICML 2019 

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Imitation Learning as $f$-Divergence Minimization

May 30, 2019
Liyiming Ke, Matt Barnes, Wen Sun, Gilwoo Lee, Sanjiban Choudhury, Siddhartha Srinivasa

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Efficient Model-free Reinforcement Learning in Metric Spaces

May 01, 2019
Zhao Song, Wen Sun

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Outcome-Driven Clustering of Acute Coronary Syndrome Patients using Multi-Task Neural Network with Attention

Mar 27, 2019
Eryu Xia, Xin Du, Jing Mei, Wen Sun, Suijun Tong, Zhiqing Kang, Jian Sheng, Jian Li, Changsheng Ma, Jianzeng Dong, Shaochun Li

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