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Doubly Optimal No-Regret Online Learning in Strongly Monotone Games with
  Bandit Feedback
v1v2v3v4 (latest)

Doubly Optimal No-Regret Online Learning in Strongly Monotone Games with Bandit Feedback

Operational Research (OR), 2021
6 December 2021
Wenjia Ba
Tianyi Lin
Jiawei Zhang
Zhengyuan Zhou
ArXiv (abs)PDFHTML

Papers citing "Doubly Optimal No-Regret Online Learning in Strongly Monotone Games with Bandit Feedback"

4 / 4 papers shown
Multi-User Contextual Cascading Bandits for Personalized Recommendation
Multi-User Contextual Cascading Bandits for Personalized Recommendation
Jiho Park
Huiwen Jia
98
0
0
19 Aug 2025
Decentralized Contextual Bandits with Network Adaptivity
Decentralized Contextual Bandits with Network Adaptivity
Chuyun Deng
Huiwen Jia
156
0
0
19 Aug 2025
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games
  with Bandit Feedback
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit FeedbackNeural Information Processing Systems (NeurIPS), 2023
Yang Cai
Haipeng Luo
Chen-Yu Wei
Weiqiang Zheng
230
24
0
05 Mar 2023
Doubly Optimal No-Regret Learning in Monotone Games
Doubly Optimal No-Regret Learning in Monotone GamesInternational Conference on Machine Learning (ICML), 2023
Yang Cai
Weiqiang Zheng
260
19
0
30 Jan 2023
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