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A Note on Zeroth-Order Optimization on the Simplex


Aug 02, 2022
Tijana Zrnic, Eric Mazumdar


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Langevin Monte Carlo for Contextual Bandits


Jun 22, 2022
Pan Xu, Hongkai Zheng, Eric Mazumdar, Kamyar Azizzadenesheli, Anima Anandkumar

* 21 pages, 3 figures, 2 tables. To appear in the proceedings of the 39th International Conference on Machine Learning (ICML2022) 

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Decentralized, Communication- and Coordination-free Learning in Structured Matching Markets


Jun 06, 2022
Chinmay Maheshwari, Eric Mazumdar, Shankar Sastry

* 41 pages, 2 figures 

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Who Leads and Who Follows in Strategic Classification?


Jun 23, 2021
Tijana Zrnic, Eric Mazumdar, S. Shankar Sastry, Michael I. Jordan


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Zeroth-Order Methods for Convex-Concave Minmax Problems: Applications to Decision-Dependent Risk Minimization


Jun 16, 2021
Chinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar, S. Shankar Sastry, Lillian J. Ratliff

* 32 pages, 5 figures 

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Fast Distributionally Robust Learning with Variance Reduced Min-Max Optimization


Apr 27, 2021
Yaodong Yu, Tianyi Lin, Eric Mazumdar, Michael I. Jordan

* The first three authors contributed equally to this work; 37 pages, 20 figures 

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Expert Selection in High-Dimensional Markov Decision Processes


Oct 26, 2020
Vicenc Rubies-Royo, Eric Mazumdar, Roy Dong, Claire Tomlin, S. Shankar Sastry

* In proceedings of the 59th IEEE Conference on Decision and Control 2020. arXiv admin note: text overlap with arXiv:1707.05714 

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Technical Report: Adaptive Control for Linearizable Systems Using On-Policy Reinforcement Learning


Apr 06, 2020
Tyler Westenbroek, Eric Mazumdar, David Fridovich-Keil, Valmik Prabhu, Claire J. Tomlin, S. Shankar Sastry


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On Thompson Sampling with Langevin Algorithms


Feb 23, 2020
Eric Mazumdar, Aldo Pacchiano, Yi-an Ma, Peter L. Bartlett, Michael I. Jordan


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Feedback Linearization for Unknown Systems via Reinforcement Learning


Oct 29, 2019
Tyler Westenbroek, David Fridovich-Keil, Eric Mazumdar, Shreyas Arora, Valmik Prabhu, S. Shankar Sastry, Claire J. Tomlin


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