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Minimax Optimization with Smooth Algorithmic Adversaries


Jun 02, 2021
Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff


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Function Design for Improved Competitive Ratio in Online Resource Allocation with Procurement Costs


Dec 23, 2020
Mitas Ray, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel


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Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks


Mar 20, 2020
Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff, Baosen Zhang


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Constrained Upper Confidence Reinforcement Learning


Jan 26, 2020
Liyuan Zheng, Lillian J. Ratliff


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Policy-Gradient Algorithms Have No Guarantees of Convergence in Continuous Action and State Multi-Agent Settings


Jul 08, 2019
Eric Mazumdar, Lillian J. Ratliff, Michael I. Jordan, S. Shankar Sastry


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Convergence of Learning Dynamics in Stackelberg Games


Jun 04, 2019
Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff


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Convergence Analysis of Gradient-Based Learning with Non-Uniform Learning Rates in Non-Cooperative Multi-Agent Settings


May 30, 2019
Benjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, Samuel A. Burden


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Competitive Statistical Estimation with Strategic Data Sources


Apr 29, 2019
Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, S. Shankar Sastry

* accepted in the IEEE Transactions on Automatic Control 

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On the Convergence of Gradient-Based Learning in Continuous Games


Sep 27, 2018
Eric Mazumdar, Lillian J. Ratliff


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Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences


Jul 06, 2018
Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff

* Published as a conference paper in Conference on Uncertainty in Artificial Intelligence (UAI) 2018 

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Incentives in the Dark: Multi-armed Bandits for Evolving Users with Unknown Type


Mar 11, 2018
Lillian J. Ratliff, Shreyas Sekar, Liyuan Zheng, Tanner Fiez


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Inverse Risk-Sensitive Reinforcement Learning


Nov 21, 2017
Lillian J. Ratliff, Eric Mazumdar

* v3 (comments regarding updates): We significantly extended the theory (Theorem 2, 3, 5 and Proposition 3). We also correct some minor typos throughout the document; v2 (comments regarding updates): We corrected some notational typos and made clarifications in the proof. We also added clarifying remarks regarding reference points and acceptance levels which were previously conflated 

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