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.

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]