Federated Linear Contextual Bandits. - Ruiquan Huang; Weiqiang Wu; Jing Yang 002; Cong Shen 001 (NeurIPS, 2021)

Cascading Bandits with Two-Level Feedback. - Duo Cheng; Ruiquan Huang; Cong Shen 001; Jing Yang 002 (ISIT, 2022)

FLORAS: Differentially Private Wireless Federated Learning Using Orthogonal Sequences. - Xizixiang Wei; Tianhao Wang 001; Ruiquan Huang; Cong Shen 001; Jing Yang 002; H. Vincent Poor (ICC, 2023)

Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs. - Yuan Cheng; Ruiquan Huang; Yingbin Liang; Jing Yang 002 (ICLR, 2023)

Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-Free RL. - Ruiquan Huang; Jing Yang 002; Yingbin Liang (ICLR, 2023)

Non-stationary Reinforcement Learning under General Function Approximation. - Songtao Feng; Ming Yin 003; Ruiquan Huang; Yu-Xiang Wang 003; Jing Yang 002; Yingbin Liang (ICML, 2023)

Federated Linear Contextual Bandits with User-level Differential Privacy. - Ruiquan Huang; Huanyu Zhang; Luca Melis; Milan Shen; Meisam Hejazinia; Jing Yang 002 (ICML, 2023)

Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints. - Donghao Li; Ruiquan Huang; Cong Shen 001; Jing Yang 002 (ICML, 2023)

Differentially Private Wireless Federated Learning Using Orthogonal Sequences. - Xizixiang Wei; Tianhao Wang 001; Ruiquan Huang; Cong Shen 001; Jing Yang 002; H. Vincent Poor (CoRR, 2023)

Temporal-Distributed Backdoor Attack against Video Based Action Recognition. - Xi Li 015; Songhe Wang; Ruiquan Huang; Mahanth Gowda; George Kesidis (AAAI, 2024)

Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes. - Ruiquan Huang; Yuan Cheng; Jing Yang 002; Vincent Tan; Yingbin Liang (ICLR, 2024)

Provably Efficient UCB-type Algorithms For Learning Predictive State Representations. - Ruiquan Huang; Yingbin Liang; Jing Yang 002 (ICLR, 2024)

Towards General Function Approximation in Nonstationary Reinforcement Learning. - Songtao Feng; Ming Yin 003; Ruiquan Huang; Yu-Xiang Wang 003; Jing Yang 002; Yingbin Liang (ISIT, 2024)

Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups. - Fengyu Gao; Ruiquan Huang; Jing Yang 002 (NeurIPS, 2024)

Non-asymptotic Convergence of Training Transformers for Next-token Prediction. - Ruiquan Huang; Yingbin Liang; Jing Yang 002 (NeurIPS, 2024)

Robust Offline Reinforcement Learning for Non-Markovian Decision Processes. - Ruiquan Huang; Yingbin Liang; Jing Yang 002 (CoRR, 2024)

Toward General Function Approximation in Nonstationary Reinforcement Learning. - Songtao Feng; Ming Yin 003; Ruiquan Huang; Yu-Xiang Wang 003; Jing Yang 002; Yingbin Liang (IEEE J. Sel. Areas Inf. Theory, 2024)

Augmenting Online RL with Offline Data is All You Need: A Unified Hybrid RL Algorithm Design and Analysis. - Ruiquan Huang; Donghao Li; Chengshuai Shi; Cong Shen 001; Jing Yang 002 (UAI, 2025)

How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias. - Ruiquan Huang; Yingbin Liang; Jing Yang 002 (CoRR, 2025)