Chung-Wei Lee

PhD Student in Computer Science at USC
Google Scholar
[email protected]

I am a final year PhD student in Computer Science at University of Southern California. I am very fortunate to be advised by Prof. Haipeng Luo. Currently, I am a research intern at DeepMind in London, hosted by Yasin Abbasi-Yadkori. I received my B.S. from National Taiwan University, double majoring in Electrical Engineering and Mathematics. My research interests lie in theoretical machine learning and algorithmic game theory.


Publications

Kernelized Multiplicative Weights for 0/1-Polyhedral Games: Bridging the Gap Between Learning in Extensive-Form and Normal-Form Games.
Gabriele Farina, Chung-Wei Lee, Haipeng Luo, Christian Kroer
International Conference on Machine Learning (ICML) 2022.
[arxiv]

Last-iterate Convergence in Extensive-form Games
Chung-Wei Lee, Christian Kroer, Haipeng Luo
Conference on Neural Information Processing Systems (NeurIPS) 2021.
[arxiv]

Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses
Haipeng Luo, Chen-Yu Wei, Chung-Wei Lee
Conference on Neural Information Processing Systems (NeurIPS) 2021.
[arxiv]

Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
International Conference on Machine Learning (ICML) 2021.
[arxiv]

Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games
Chen-Yu Wei, Chung-Wei Lee, Mengxiao Zhang, Haipeng Luo
Annual Conference on Learning Theory (COLT) 2021.
[arxiv]

Linear Last-iterate Convergence in Constrained Saddle-point Optimization
Chen-Yu Wei, Chung-Wei Lee, Mengxiao Zhang, Haipeng Luo
Conference on Learning Representations (ICLR) 2021.
[arxiv]

Bias No More: High-probability Data-dependent Regret Bounds for Adversarial Bandits and MDPs
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang
Conference on Neural Information Processing Systems (NeurIPS) 2020. (Oral)
[arxiv]


A Closer Look at Small-loss Bounds for Bandits with Graph Feedback
Chung-Wei Lee, Haipeng Luo, Mengxiao Zhang
Annual Conference on Learning Theory (COLT) 2020.
[arxiv]


A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal, and Parameter-free
Yifang Chen, Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei
Annual Conference on Learning Theory (COLT) 2019.
[arxiv]

Multi-Label Zero-Shot Learning with Structured Knowledge Graphs
Chung-Wei Lee, Wei Fang, Chih-Kuan Yeh, Yu-Chiang Frank Wang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018.
[arxiv]