publications

2025

1. Robust Offline Reinforcement Learning for Non-Markovian Decision Processes

   Ruiquan Huang, Yingbin Liang, and Jing Yang

   IEEE Transactions on Information Theory, 2025

   DOI
2. Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis

   Ruiquan Huang, Donghao Li, Chengshuai Shi, and 2 more authors

   In Conference on Uncertainty in Artificial Intelligence (UAI), 2025
3. How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias

   Ruiquan Huang, Yingbin Liang, and Jing Yang

   In International Conference on Machine Learning (ICML), 2025

2024

1. Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups

   Fengyu Gao, Ruiquan Huang, and Jing Yang

   In The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024
2. Temporal-distributed backdoor attack against video based action recognition

   Xi Li, Songhe Wang, Ruiquan Huang, and 2 more authors

   In Proceedings of the AAAI Conference on Artificial Intelligence, 2024
3. Provably efficient ucb-type algorithms for learning predictive state representations

   Ruiquan Huang, Yingbin Liang, and Jing Yang

   12th International Conference on Learning Representations (ICLR), 2024
4. Non-asymptotic Convergence of Training Transformers for Next-token Prediction

   Ruiquan Huang, Yingbin Liang, and Jing Yang

   The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024
5. Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes

   Ruiquan Huang, Yuan Cheng, Jing Yang, and 2 more authors

   12th International Conference on Learning Representations (ICLR), 2024
6. Robust Offline Reinforcement Learning for Non-Markovian Decision Processes

   Ruiquan Huang, Yingbin Liang, and Jing Yang

   arXiv preprint arXiv:2411.07514, 2024
7. Towards General Function Approximation in Nonstationary Reinforcement Learning

   Songtao Feng, Ming Yin, Ruiquan Huang, and 3 more authors

   IEEE Journal on Selected Areas in Information Theory, 2024

2023

1. Federated linear contextual bandits with user-level differential privacy

   Ruiquan Huang, Huanyu Zhang, Luca Melis, and 3 more authors

   In International Conference on Machine Learning (ICML), 2023
2. Improved sample complexity for reward-free reinforcement learning under low-rank mdps

   Yuan Cheng, Ruiquan Huang, Jing Yang, and 1 more author

   11th International Conference on Learning Representations (ICLR), 2023
3. Non-stationary reinforcement learning under general function approximation

   Songtao Feng, Ming Yin, Ruiquan Huang, and 3 more authors

   In International Conference on Machine Learning (ICML), 2023
4. Safe exploration incurs nearly no additional sample complexity for reward-free rl

   Ruiquan Huang, Jing Yang, and Yingbin Liang

   11th International Conference on Learning Representations (ICLR), 2023
5. FLORAS: Differentially private wireless federated learning using orthogonal sequences

   Xizixiang Wei, Tianhao Wang, Ruiquan Huang, and 3 more authors

   In ICC 2023-IEEE International Conference on Communications, 2023
6. Near-optimal conservative exploration in reinforcement learning under episode-wise constraints

   Donghao Li, Ruiquan Huang, Cong Shen, and 1 more author

   In International Conference on Machine Learning, 2023

2022

1. Cascading bandits with two-level feedback

   Duo Cheng, Ruiquan Huang, Cong Shen, and 1 more author

   In 2022 IEEE International Symposium on Information Theory (ISIT), 2022

2021

1. Federated linear contextual bandits

   Ruiquan Huang, Weiqiang Wu, Jing Yang, and 1 more author

   Advances in neural information processing systems, 2021