Haipeng Luo
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IBM Early Career Chair and Associate Professor Office: SAL 216 |
About me
I am an associate professor in the Thomas Lord Department of Computer Science at the University of Southern California. Previously I spent one year at Microsoft Research, NYC as a postdoctoral researcher. I obtained my PhD from Princeton University, where I was fortunate enough to be advised by Rob Schapire and also to work closely with Elad Hazan. I received my bachelor degree at Peking University working with Professor Zhen Xiao.
Research interests
My research interest is in developing practical machine learning algorithms with strong theoretical guarantees, with a focus on
online learning
bandit problems
reinforcement learning
learning in games
fast and scalable optimization methods
See below for some of my representative papers (a full list can be found here or at Google Scholar).
Representative Papers
[COLT 2021 Best Paper Award] Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach.
Chen-Yu Wei and Haipeng Luo.
[NeurIPS 2021 Oral] The Best of Both Worlds: Stochastic and Adversarial Episodic MDPs with Unknown Transition.
Tiancheng Jin, Longbo Huang, and Haipeng Luo.
[NeurIPS 2020 Oral] Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs.
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, and Mengxiao Zhang.
[COLT 2018 Best Student Paper Award] Logistic Regression: The Importance of Being Improper.
Dylan J. Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, and Karthik Sridharan.
[COLT 2018] More Adaptive Algorithms for Adversarial Bandits.
Chen-Yu Wei and Haipeng Luo.
[COLT 2017] Corralling a Band of Bandit Algorithms.
Alekh Agarwal, Haipeng Luo, Behnam Neyshabur, and Robert E. Schapire.
[NeurIPS 2015 Best Paper Award] Fast Convergence of Regularized Learning in Games.
Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo, and Robert E. Schapire.
[ICML 2015 Best Paper Award] Optimal and Adaptive Algorithms for Online Boosting.
Alina Beygelzimer, Satyen Kale, and Haipeng Luo.
[COLT 2015] Achieving All with No Parameters: AdaNormalHedge.
Haipeng Luo and Robert E. Schapire.