Publications
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(* stands for equal contribution. Listed in reverse chronological order.)
Conference Publications
- [COLT 2024] Refined Sample Complexity for Markov Games with Independent Linear Function Approximation
Yan Dai, Qiwen Cui, and Simon S. Du.
Accepted to the 37th Annual Conference on Learning Theory (COLT), 2024. - [ICML 2024] Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise
Kwangjun Ahn, Zhiyu Zhang, Yunbum Kook, and Yan Dai.
Accepted to the 41st International Conference on Machine Learning (ICML), 2024. - [NeurIPS 2023] The Crucial Role of Normalization in Sharpness-Aware Minimization
Yan Dai*, Kwangjun Ahn*, and Suvrit Sra.
In Advances in Neural Information Processing Systems 36 (NeurIPS), 2023.
(slides, video) - [ICML 2023] Refined Regret for Adversarial MDPs with Linear Function Approximation
Yan Dai, Haipeng Luo, Chen-Yu Wei, and Julian Zimmert.
In Proceedings of the 40th International Conference on Machine Learning (ICML), 2023.
(slides (long), slides (short), video) - [ICML 2023] Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning
Jiatai Huang*, Yan Dai*, and Longbo Huang.
In Proceedings of the 40th International Conference on Machine Learning (ICML), 2023.
(slides, video) - [ICLR 2023] Variance-Aware Sparse Linear Bandits
Yan Dai, Ruosong Wang, and Simon S. Du.
In the Eleventh International Conference on Learning Representations (ICLR), 2023.
(slides (long), slides (short), video) - [NeurIPS 2022] Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback
Yan Dai, Haipeng Luo, and Liyu Chen.
In Advances in Neural Information Processing Systems 35 (NeurIPS), 2022.
(slides, video) - [ICML 2022] Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits
Jiatai Huang*, Yan Dai*, and Longbo Huang.
In Proceedings of the 39th International Conference on Machine Learning (ICML), 2022.
(video)