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Weiqiang Zheng
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2020 – today
- 2024
- [c11]Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng:
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games. AISTATS 2024: 3889-3897 - [c10]Jiahao Zhang, Tao Lin, Weiqiang Zheng, Zhe Feng, Yifeng Teng, Xiaotie Deng:
Learning Thresholds with Latent Values and Censored Feedback. ICLR 2024 - [c9]Yang Cai, Argyris Oikonomou, Weiqiang Zheng:
Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion. ICML 2024 - [i13]Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng:
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games. CoRR abs/2401.15240 (2024) - [i12]Yang Cai, Constantinos Daskalakis, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng:
Tractable Local Equilibria in Non-Concave Games. CoRR abs/2403.08171 (2024) - [i11]Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng:
Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms. CoRR abs/2406.10631 (2024) - 2023
- [c8]Yang Cai, Weiqiang Zheng:
Accelerated Single-Call Methods for Constrained Min-Max Optimization. ICLR 2023 - [c7]Yang Cai, Weiqiang Zheng:
Doubly Optimal No-Regret Learning in Monotone Games. ICML 2023: 3507-3524 - [c6]Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng:
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback. NeurIPS 2023 - [i10]Yang Cai, Weiqiang Zheng:
Doubly Optimal No-Regret Learning in Monotone Games. CoRR abs/2301.13120 (2023) - [i9]Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng:
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games. CoRR abs/2303.02738 (2023) - [i8]Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng:
Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games. CoRR abs/2311.00676 (2023) - [i7]Jiahao Zhang, Tao Lin, Weiqiang Zheng, Zhe Feng, Yifeng Teng, Xiaotie Deng:
Learning Thresholds with Latent Values and Censored Feedback. CoRR abs/2312.04653 (2023) - 2022
- [c5]Dezhi Ran, Weiqiang Zheng, Yunqi Li, Kaigui Bian, Jie Zhang, Xiaotie Deng:
Revenue and User Traffic Maximization in Mobile Short-Video Advertising. AAMAS 2022: 1092-1100 - [c4]Yang Cai, Argyris Oikonomou, Weiqiang Zheng:
Finite-Time Last-Iterate Convergence for Learning in Multi-Player Games. NeurIPS 2022 - [c3]Lirong Xia, Weiqiang Zheng:
Beyond the Worst Case: Semi-random Complexity Analysis of Winner Determination. WINE 2022: 330-347 - [c2]Xiaotie Deng, Xinyan Hu, Tao Lin, Weiqiang Zheng:
Nash Convergence of Mean-Based Learning Algorithms in First Price Auctions. WWW 2022: 141-150 - [i6]Yang Cai, Argyris Oikonomou, Weiqiang Zheng:
Tight Last-Iterate Convergence of the Extragradient Method for Constrained Monotone Variational Inequalities. CoRR abs/2204.09228 (2022) - [i5]Yang Cai, Argyris Oikonomou, Weiqiang Zheng:
Accelerated Algorithms for Monotone Inclusions and Constrained Nonconvex-Nonconcave Min-Max Optimization. CoRR abs/2206.05248 (2022) - [i4]Yang Cai, Weiqiang Zheng:
Accelerated Single-Call Methods for Constrained Min-Max Optimization. CoRR abs/2210.03096 (2022) - [i3]Lirong Xia, Weiqiang Zheng:
Beyond the Worst Case: Semi-Random Complexity Analysis of Winner Determination. CoRR abs/2210.08173 (2022) - 2021
- [c1]Lirong Xia, Weiqiang Zheng:
The Smoothed Complexity of Computing Kemeny and Slater Rankings. AAAI 2021: 5742-5750 - [i2]Xiaotie Deng, Xinyan Hu, Tao Lin, Weiqiang Zheng:
Nash Convergence of Mean-Based Learning Algorithms in First Price Auctions. CoRR abs/2110.03906 (2021) - 2020
- [i1]Lirong Xia, Weiqiang Zheng:
The Smoothed Complexity of Computing Kemeny and Slater Rankings. CoRR abs/2010.13020 (2020)
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