Zhang, Zihan

27 publications

ICLR 2025 Almost Optimal Batch-Regret Tradeoff for Batch Linear Contextual Bandits Zihan Zhang, Xiangyang Ji, Yuan Zhou

COLT 2025 Anytime Acceleration of Gradient Descent Zihan Zhang, Jason Lee, Simon Du, Yuxin Chen

NeurIPS 2025 Deployment Efficient Reward-Free Exploration with Linear Function Approximation Zihan Zhang, Yuxin Chen, Jason D. Lee, Simon Shaolei Du, Lin Yang, Ruosong Wang

ICML 2025 Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback Zihan Zhang, Yuxin Chen, Jason D. Lee, Simon Shaolei Du, Ruosong Wang

NeurIPS 2025 Sharp Gap-Dependent Variance-Aware Regret Bounds for Tabular MDPs Shulun Chen, Runlong Zhou, Zihan Zhang, Maryam Fazel, Simon Shaolei Du

NeurIPS 2024 Achieving Tractable Minimax Optimal Regret in Average Reward MDPs Victor Boone, Zihan Zhang

JMLR 2024 Classification with Deep Neural Networks and Logistic Loss Zihan Zhang, Lei Shi, Ding-Xuan Zhou

ICLR 2024 Horizon-Free Regret for Linear Markov Decision Processes Zihan Zhang, Jason D. Lee, Yuxin Chen, Simon Shaolei Du

COLT 2024 Optimal Multi-Distribution Learning Zihan Zhang, Wenhao Zhan, Yuxin Chen, Simon S Du, Jason D Lee

COLT 2024 Settling the Sample Complexity of Online Reinforcement Learning Zihan Zhang, Yuxin Chen, Jason D Lee, Simon S Du

AAAI 2024 Text Diffusion with Reinforced Conditioning Yuxuan Liu, Tianchi Yang, Shaohan Huang, Zihan Zhang, Haizhen Huang, Furu Wei, Weiwei Deng, Feng Sun, Qi Zhang

ECCV 2024 Vision-Language Dual-Pattern Matching for Out-of-Distribution Detection Zihan Zhang, Zhuo Xu, Xiang Xiang

CVPR 2023 Decoupling MaxLogit for Out-of-Distribution Detection Zihan Zhang, Xiang Xiang

NeurIPS 2023 Open Visual Knowledge Extraction via Relation-Oriented Multimodality Model Prompting Hejie Cui, Xinyu Fang, Zihan Zhang, Ran Xu, Xuan Kan, Xin Liu, Yue Yu, Manling Li, Yangqiu Song, Carl Yang

COLT 2023 Sharper Model-Free Reinforcement Learning for Average-Reward Markov Decision Processes Zihan Zhang, Qiaomin Xie

COLT 2022 Horizon-Free Reinforcement Learning in Polynomial Time: The Power of Stationary Policies Zihan Zhang, Xiangyang Ji, Simon Du

NeurIPS 2022 Near-Optimal Regret Bounds for Multi-Batch Reinforcement Learning Zihan Zhang, Yuhang Jiang, Yuan Zhou, Xiangyang Ji

NeurIPS 2021 Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP Zihan Zhang, Jiaqi Yang, Xiangyang Ji, Simon S Du

COLT 2021 Is Reinforcement Learning More Difficult than Bandits? a Near-Optimal Algorithm Escaping the Curse of Horizon Zihan Zhang, Xiangyang Ji, Simon Du

AAAI 2021 Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks Zhiliang Tian, Wei Bi, Zihan Zhang, Dongkyu Lee, Yiping Song, Nevin L. Zhang

ICML 2021 Model-Free Reinforcement Learning: From Clipped Pseudo-Regret to Sample Complexity Zihan Zhang, Yuan Zhou, Xiangyang Ji

ICML 2021 Near Optimal Reward-Free Reinforcement Learning Zihan Zhang, Simon Du, Xiangyang Ji

NeurIPS 2020 Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage Decomposition Zihan Zhang, Yuan Zhou, Xiangyang Ji

IJCAI 2020 Argot: Generating Adversarial Readable Chinese Texts Zihan Zhang, Mingxuan Liu, Chao Zhang, Yiming Zhang, Zhou Li, Qi Li, Haixin Duan, Donghong Sun

NeurIPS 2019 AttentionXML: Label Tree-Based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification Ronghui You, Zihan Zhang, Ziye Wang, Suyang Dai, Hiroshi Mamitsuka, Shanfeng Zhu

NeurIPS 2019 Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function Zihan Zhang, Xiangyang Ji

AAAI 2016 Multi-Domain Active Learning for Recommendation Zihan Zhang, Xiaoming Jin, Lianghao Li, Guiguang Ding, Qiang Yang