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07/03/2023
Coupled Gradient Flows for Strategic Non-Local Distribution Shift
We propose a novel framework for analyzing the dynamics of distribution ...
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03/03/2023
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games
We study two-player zero-sum stochastic games, and propose a form of ind...
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02/08/2023
Algorithmic Collective Action in Machine Learning
We initiate a principled study of algorithmic collective action on digit...
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02/02/2023
Convergent First-Order Methods for Bi-level Optimization and Stackelberg Games
We propose an algorithm to solve a class of bi-level optimization proble...
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08/02/2022
A Note on Zeroth-Order Optimization on the Simplex
We construct a zeroth-order gradient estimator for a smooth function def...
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06/22/2022
Langevin Monte Carlo for Contextual Bandits
We study the efficiency of Thompson sampling for contextual bandits. Exi...
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06/06/2022
Decentralized, Communication- and Coordination-free Learning in Structured Matching Markets
We study the problem of online learning in competitive settings in the c...
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06/23/2021
Who Leads and Who Follows in Strategic Classification?
As predictive models are deployed into the real world, they must increas...
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06/16/2021
Zeroth-Order Methods for Convex-Concave Minmax Problems: Applications to Decision-Dependent Risk Minimization
Min-max optimization is emerging as a key framework for analyzing proble...
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04/27/2021
Fast Distributionally Robust Learning with Variance Reduced Min-Max Optimization
Distributionally robust supervised learning (DRSL) is emerging as a key ...
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10/26/2020
Expert Selection in High-Dimensional Markov Decision Processes
In this work we present a multi-armed bandit framework for online expert...
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04/06/2020
Technical Report: Adaptive Control for Linearizable Systems Using On-Policy Reinforcement Learning
This paper proposes a framework for adaptively learning a feedback linea...
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02/23/2020
On Thompson Sampling with Langevin Algorithms
Thompson sampling is a methodology for multi-armed bandit problems that ...
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02/03/2020
Local Nash Equilibria are Isolated, Strict Local Nash Equilibria in `Almost All' Zero-Sum Continuous Games
We prove that differential Nash equilibria are generic amongst local Nas...
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10/29/2019
Feedback Linearization for Unknown Systems via Reinforcement Learning
We present a novel approach to control design for nonlinear systems, whi...
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07/08/2019
Policy-Gradient Algorithms Have No Guarantees of Convergence in Continuous Action and State Multi-Agent Settings
We show by counterexample that policy-gradient algorithms have no guaran...
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05/30/2019
Convergence Analysis of Gradient-Based Learning with Non-Uniform Learning Rates in Non-Cooperative Multi-Agent Settings
Considering a class of gradient-based multi-agent learning algorithms in...
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04/16/2018
On the Convergence of Competitive, Multi-Agent Gradient-Based Learning
As learning algorithms are increasingly deployed in markets and other co...
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03/29/2017
