• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 51 matches

• 2023
• 
  Jiafan He, Aiguo Fei, Qingwei Li, Feng Fang:
  Attitude Synchronization of Heterogenous Flexible Spacecrafts by Measurement-Based Feedback With Disturbance Suppression. IEEE Access 11: 84453-84467 (2023)
• 
  Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu:
  Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency. COLT 2023: 4977-5020
• 
  Qiwei Di, Jiafan He, Dongruo Zhou, Quanquan Gu:
  Nearly Minimax Optimal Regret for Learning Linear Mixture Stochastic Shortest Path. ICML 2023: 7837-7864
• 
  Jiafan He, Heyang Zhao, Dongruo Zhou, Quanquan Gu:
  Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes. ICML 2023: 12790-12822
• 
  Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu:
  Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. ICML 2023: 24785-24811
• 
  Weitong Zhang, Jiafan He, Zhiyuan Fan, Quanquan Gu:
  On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits. ICML 2023: 41111-41132
• 
  Heyang Zhao, Dongruo Zhou, Jiafan He, Quanquan Gu:
  Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits. ICML 2023: 42259-42279
• 
  Yue Wu, Jiafan He, Quanquan Gu:
  Uniform-PAC Guarantees for Model-Based RL with Bounded Eluder Dimension. UAI 2023: 2304-2313
• 
  Weitong Zhang, Jiafan He, Dongruo Zhou, Amy Zhang, Quanquan Gu:
  Provably efficient representation selection in Low-rank Markov Decision Processes: from online to offline RL. UAI 2023: 2488-2497
• 
  Heyang Zhao, Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu:
  Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency. CoRR abs/2302.10371 (2023)
• 
  Weitong Zhang, Jiafan He, Zhiyuan Fan, Quanquan Gu:
  On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits. CoRR abs/2303.09390 (2023)
• 
  Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu:
  Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. CoRR abs/2305.06446 (2023)
• 
  Yue Wu, Jiafan He, Quanquan Gu:
  Uniform-PAC Guarantees for Model-Based RL with Bounded Eluder Dimension. CoRR abs/2305.08350 (2023)
• 
  Kaixuan Ji, Qingyue Zhao, Jiafan He, Weitong Zhang, Quanquan Gu:
  Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs. CoRR abs/2305.08359 (2023)
• 
  Qiwei Di, Heyang Zhao, Jiafan He, Quanquan Gu:
  Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning. CoRR abs/2310.01380 (2023)
• 
  Heyang Zhao, Jiafan He, Quanquan Gu:
  A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation. CoRR abs/2311.15238 (2023)
• 2022
• 
  Jiaqi Wang, Wei Xing Zheng, Andong Sheng, Jiafan He:
  Cooperative Global Robust Practical Output Regulation of Nonlinear Lower Triangular Multiagent Systems via Event-Triggered Control. IEEE Trans. Cybern. 52(7): 5708-5719 (2022)
• 
  Chonghua Liao, Jiafan He, Quanquan Gu:
  Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes. ACML 2022: 627-642
• 
  Jiafan He, Dongruo Zhou, Quanquan Gu:
  Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs. AISTATS 2022: 4259-4280
• 
  Yiming Mao, Zhijie Xia, Qingwei Li, Jiafan He, Aiguo Fei:
  Accurate Decision-Making Method for Air Combat Pilots Based on Data-Driven. DMBD (2) 2022: 439-448
• 
  Yuanzhou Chen, Jiafan He, Quanquan Gu:
  On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPs. ICML 2022: 3149-3183
• 
  Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu:
  Learning Stochastic Shortest Path with Linear Function Approximation. ICML 2022: 15584-15629
• 
  Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu:
  A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. NeurIPS 2022
• 
  Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu:
  Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions. NeurIPS 2022
• 
  Heyang Zhao, Dongruo Zhou, Jiafan He, Quanquan Gu:
  Bandit Learning with General Function Classes: Heteroscedastic Noise and Variance-dependent Regret Bounds. CoRR abs/2202.13603 (2022)
• 
  Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu:
  Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions. CoRR abs/2205.06811 (2022)
• 
  Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu:
  A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. CoRR abs/2207.03106 (2022)
• 
  Jiafan He, Heyang Zhao, Dongruo Zhou, Quanquan Gu:
  Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes. CoRR abs/2212.06132 (2022)
• 2021
• 
  Jiafan He, Dongruo Zhou, Quanquan Gu:
  Logarithmic Regret for Reinforcement Learning with Linear Function Approximation. ICML 2021: 4171-4180
• 
  Dongruo Zhou, Jiafan He, Quanquan Gu:
  Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping. ICML 2021: 12793-12802

skipping 21 more matches