paper-conference

On Tractable $\Phi$-Equilibria in Non-Concave Games
Yang Cai, Constantinos Daskalakis, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
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Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms
Yang Cai, Gabriele Farian, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng
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Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games
We study policy optimization algorithms for computing correlated equilibria in multi-player general-sum Markov Games. Previous results …
Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
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Learning Thresholds with Latent Values and Censored Feedback
In this paper, we investigate a problem of actively learning threshold in latent space, where the unknown reward $g(\gamma, v)$ …
(*) Jiahao Zhang, Tao Lin, Weiqiang Zheng, Zhe Feng, Yifeng Teng, Xiaotie Deng
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Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback
We revisit the problem of learning in two-player zero-sum Markov games, focusing on developing an algorithm that is uncoupled, …
Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng
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Doubly Optimal No-Regret Learning in Monotone Games
We consider online learning in multi-player smooth monotone games. Existing algorithms have limitations such as (1) being only …
Yang Cai, Weiqiang Zheng
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Accelerated Single-Call Methods for Constrained Min-Max Optimization
We study first-order methods for constrained min-max optimization. Existing methods either require two gradient calls or two …
Yang Cai, Weiqiang Zheng
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Beyond the Worst Case: Semi-random Complexity Analysis of Winner Determination
The computational complexity of winner determination is a classical and important problem in computational social choice. Previous work …
Lirong Xia, Weiqiang Zheng
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Finite-Time Last-Iterate Convergence for Learning in Multi-Player Games
We study the question of last-iterate convergence rate of the extragradient algorithm by Korpelevich [1976] and the optimistic gradient …
Yang Cai, Argyris Oikonomou, Weiqiang Zheng
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Nash Convergence of Mean-Based Learning Algorithms in First Price Auctions
Understanding the convergence properties of learning dynamics in repeated auctions is a timely and important question in the area of …
Xiaotie Deng, Xinyan Hu, Tao Lin, Weiqiang Zheng
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