Yuanhao Wang yuanhao at princeton dot edu [Google Scholar][Twitter][Curriculum Vitae] I am a fifth and final year PhD student at the Computer Science Department of Princeton University. I am fortunate to be advised by Chi Jin. Before that, I received my bachelor's degree from Yao Class at Tsinghua University. My research interests include reinforcement learning theory, learning in games and minimax optimization.

Selected Publications

Learning in Games

• V-Learning – A Simple, Efficient, Decentralized Algorithm for Multiagent RL [arxiv]

  • Chi Jin, Qinghua Liu, Yuanhao Wang, Tiancheng Yu (α-β order)

  • Mathematics of Operations Research, Best Paper in ICLR 2022 “Gamification and Multiagent Solutions” workshop

• Learning markov games with adversarial opponents: Efficient algorithms and fundamental limits [arxiv]

  • Qinghua Liu*, Yuanhao Wang*, Chi Jin
    

  • ICML 2022 (oral)

RL with Function Approximation

• An Exponential Lower Bound for Linearly Realizable MDP with Constant Suboptimality Gap [arxiv]

  • Yuanhao Wang, Ruosong Wang, Sham M. Kakade

  • NeurIPS 2021 (oral)

• Is RLHF more Difficult than Standard RL? A Theoretical Perspective [arxiv]

  • Yuanhao Wang, Qinghua Liu, Chi Jin

  • NeurIPS 2023

Minimax Optimization

• On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach [arxiv]

  • Yuanhao Wang*, Guodong Zhang*, Jimmy Ba

  • ICLR 2020, invited talk at NeurIPS 2019 [Smooth Games Optimization and Machine Learning Workshop]

• Improved Algorithms for Convex-Concave Minimax Optimization [arxiv]

  • Yuanhao Wang, Jian Li

  • NeurIPS 2020

Services

Reviewer for: ICML, NeurIPS, ICLR, AISTATS, COLT, etc.