Liu, Qinghua

19 publications

ICML 2025 Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment Audrey Huang, Adam Block, Qinghua Liu, Nan Jiang, Akshay Krishnamurthy, Dylan J Foster

ICLR 2025 The Belief State Transformer Edward S. Hu, Kwangjun Ahn, Qinghua Liu, Haoran Xu, Manan Tomar, Ada Langford, Dinesh Jayaraman, Alex Lamb, John Langford

ACML 2024 DCoT: Dual Chain-of-Thought Prompting for Large Multimodal Models Zixi Jia, Jiqiang Liu, Hexiao Li, Qinghua Liu, Hongbin Gao

NeurIPS 2024 The Elephant in the Room: Towards a Reliable Time-Series Anomaly Detection Benchmark Qinghua Liu, John Paparrizos

COLT 2023 Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation Yuanhao Wang, Qinghua Liu, Yu Bai, Chi Jin

NeurIPS 2023 Context-Lumpable Stochastic Bandits Chung-Wei Lee, Qinghua Liu, Yasin Abbasi Yadkori, Chi Jin, Tor Lattimore, Csaba Szepesvari

NeurIPS 2023 Is RLHF More Difficult than Standard RL? a Theoretical Perspective Yuanhao Wang, Qinghua Liu, Chi Jin

NeurIPS 2023 Optimistic Natural Policy Gradient: A Simple Efficient Policy Optimization Framework for Online RL Qinghua Liu, Gellert Weisz, András György, Chi Jin, Csaba Szepesvari

ICML 2022 Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits Qinghua Liu, Yuanhao Wang, Chi Jin

NeurIPS 2022 Policy Optimization for Markov Games: Unified Framework and Faster Convergence Runyu Zhang, Qinghua Liu, Huan Wang, Caiming Xiong, Na Li, Yu Bai

NeurIPS 2022 Sample-Efficient Reinforcement Learning of Partially Observable Markov Games Qinghua Liu, Csaba Szepesvari, Chi Jin

ICML 2022 The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces Chi Jin, Qinghua Liu, Tiancheng Yu

ICLRW 2022 V-Learning -- a Simple, Efficient, Decentralized Algorithm for Multiagent RL Chi Jin, Qinghua Liu, Yuanhao Wang, Tiancheng Yu

COLT 2022 When Is Partially Observable Reinforcement Learning Not Scary? Qinghua Liu, Alan Chung, Csaba Szepesvari, Chi Jin

ICML 2021 A Sharp Analysis of Model-Based Reinforcement Learning with Self-Play Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin

NeurIPS 2021 Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms Chi Jin, Qinghua Liu, Sobhan Miryoosefi

ICLR 2021 Provable Rich Observation Reinforcement Learning with Combinatorial Latent States Dipendra Misra, Qinghua Liu, Chi Jin, John Langford

NeurIPS 2020 Sample-Efficient Reinforcement Learning of Undercomplete POMDPs Chi Jin, Sham Kakade, Akshay Krishnamurthy, Qinghua Liu

NeurIPS 2020 Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi, H. Vincent Poor