Hao Liang



Optimistic Thompson Sampling for No-regret Learning in Unknown Games [link] IEEE TSP
Yingru Li, Liangqi Liu, Wenqiang Pu, Hao Liang, Zhi-Quan Luo


How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models? [link] ICML 2026
Xiaoyuan Cheng, Wenxuan Yuan, Boyang Li, Yuanchao Xu, Yiming Yang, Hao Liang, Bei Peng, Robert Loftin, Zhuo Sun, Yukun Hu


Is Pure Exploitation Sufficient in Exogenous MDPs with Linear Function Approximation? [link] ICLR 2026
Hao Liang, Jiayu Cheng, Sean R. Sinclair, Yali Du


BRIDGE: Bi-level Reinforcement Learning for Dynamic Group Structure in Coalition Formation Games ICLR 2026
Shuqing Shi, Nam Phuong Tran, Hao Liang, Debmalya Mandal, Long Tran-Thanh, Yali Du


Causality Meets Locality: Provably Generalizable and Scalable Policy Learning for Networked Systems [link] NeurIPS 2025 (Spotlight)
Hao Liang*, Shuqing Shi*, Yudi Zhang, Biwei Huang, Yali Du


Why GRPO Needs Normalization: A Local-Curvature Perspective on Adaptive Gradients To appear
Cheng Ge*, Heqi Yin*, Hao Liang, Jiawei Zhang
* Equal contribution. † Co-last/corresponding authors.
Presented at NeurIPS 2025 Workshop on Efficient Reasoning.


Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds [link] JMLR
Hao Liang, Zhi-Quan Luo
Presented at NeurIPS 2025 (The NeurIPS/ICLR/ICML Journal-to-Conference Track). An earlier version presented at NeurIPS 2021 Workshop on Ecological Theory of RL

Bridging Distributional and Risk-Sensitive Reinforcement Learning: Balancing Statistical, Computational, and Risk Considerations [link]
Hao Liang
Presented at ICML 2024 Workshop on FoRLaC

Regret Bounds for Risk-sensitive Reinforcement Learning with Lipschitz Dynamic Risk Measures [AISTATS] AISTATS 2024
Hao Liang, Zhi-Quan Luo
An earlier version presented at ICML 2023 Workshop on New Frontiers in Learning, Control, and Dynamical Systems

A Distribution Optimization Framework for Confidence Bounds of Risk Measures [ICML] ICML 2023
Hao Liang, Zhi-Quan Luo


Working Papers


Revisiting Minimax Lower Bounds in Unknown Matrix Game
Hao Liang, Yingru Li