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RESEARCH PAPER · arXiv (Cornell University) · 2019

Provably Efficient Q-Learning with Low Switching Cost

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23 direct citing papers in this saved network. Explore the next layer with second-order citations.

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42 direct citing works

Provably Efficient Q-Learning with Low Switching CostOriginalOnline Batch Decision-Making with High-Dimensional Covariates2Collaborative Top Distribution Identifications with Limited Interaction2Generalized Optimistic Q-Learning with Provable Efficiency5Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization50Model-Free Non-Stationary RL: Near-Optimal Regret and Applications in Multi-Agent RL and Inventory Control8Collaborative Top Distribution Identifications with Limited Interaction (Extended Abstract)10Near-Optimal Offline Reinforcement Learning via Double Variance Reduction18MUSBO: Model-based Uncertainty Regularized and Sample Efficient Batch Optimization for Deployment Constrained Reinforcement Learning5Homomorphically Encrypted Linear Contextual Bandit.1Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning16Safe Reinforcement Learning with Linear Function Approximation2Online Sub-Sampling for Reinforcement Learning with General Function Approximation2Linear bandits with limited adaptivity and learning distributional optimal design20Design of Experiments for Stochastic Contextual Linear Bandits3Batched Thompson Sampling for Multi-Armed Bandits0Understanding Domain Randomization for Sim-to-real Transfer33Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration3Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction60Breaking the sample complexity barrier to regret-optimal model-free reinforcement learning12Predicting Potential Risk: Cerebral Stroke via Regret Minimization0Settling the sample complexity of model-based offline reinforcement learning22Cooperative Markov Decision Process model for human–machine co-adaptation in robot-assisted rehabilitation6Sample Efficient Reinforcement Learning with Partial Dynamics Knowledge2

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  1. Online Batch Decision-Making with High-Dimensional Covariates

    arXiv (Cornell University) · 2020-02-21

    Chi‐Hua Wang, Guang Cheng

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  2. Collaborative Top Distribution Identifications with Limited Interaction

    arXiv (Cornell University) · 2020-04-20

    Karpov, Nikolai, Qin Zhang, Yuan Zhou

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  3. Generalized Optimistic Q-Learning with Provable Efficiency

    Adaptive Agents and Multi-Agents Systems · 2020-05-05

    G. V. Neustroev, Mathijs M. De Weerdt

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  4. Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization

    arXiv (Cornell University) · 2020-06-05

    Tatsuya Matsushima, Hiroki Furuta, Yutaka Matsuo, Ofir Nachum, Shixiang Gu

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  5. Model-Free Non-Stationary RL: Near-Optimal Regret and Applications in Multi-Agent RL and Inventory Control

    arXiv (Cornell University) · 2020-10-07

    Weichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi‐Levi, Tamer Başar

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  6. Collaborative Top Distribution Identifications with Limited Interaction (Extended Abstract)

    Annual Symposium on Foundations of Computer Science · 2020-11-01

    Nikolai Karpov, Qin Zhang, Yuan Zhou

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  7. Near-Optimal Offline Reinforcement Learning via Double Variance Reduction

    arXiv (Cornell University) · 2021-02-02

    Minghao Yin, Yu Bai, Yu-Xiang Wang

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  8. MUSBO: Model-based Uncertainty Regularized and Sample Efficient Batch Optimization for Deployment Constrained Reinforcement Learning

    arXiv (Cornell University) · 2021-02-23

    DiJia Su, Jason D. Lee, John M. Mulvey, H. Vincent Poor

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  9. Homomorphically Encrypted Linear Contextual Bandit.

    arXiv (Cornell University) · 2021-03-17

    Evrard Garcelon, Vianney Perchet, Matteo Pirotta

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  10. Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning

    arXiv (Cornell University) · 2021-06-09

    Tengyang Xie, Jiang, Nan, Huan Wang, Caiming Xiong, Yu Bai

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  11. Safe Reinforcement Learning with Linear Function Approximation

    arXiv (Cornell University) · 2021-06-11

    Sanae Amani, Christos Thrampoulidis, Lin Forrest Yang

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  12. Online Sub-Sampling for Reinforcement Learning with General Function Approximation

    arXiv (Cornell University) · 2021-06-14

    Dingwen Kong, Ruslan Salakhutdinov, Ruosong Wang, Lin Forrest Yang

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  13. Linear bandits with limited adaptivity and learning distributional optimal design

    ACM SIGACT Symposium on Theory of Computing (STOC) · 2021-06-15

    Yufei Ruan, Jiaqi Yang, Yuan Zhou

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  14. Design of Experiments for Stochastic Contextual Linear Bandits

    arXiv (Cornell University) · 2021-07-21

    Andrea Zanette, Kefan Dong, Jonathan H. Lee, Emma Brunskill

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  15. Batched Thompson Sampling for Multi-Armed Bandits

    arXiv (Cornell University) · 2021-08-15

    Karpov, Nikolai, Qin Zhang

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  16. Understanding Domain Randomization for Sim-to-real Transfer

    arXiv (Cornell University) · 2021-10-07

    Xiaoyu Chen, Jiachen Hu, Chi Jin, Lihong Li, Liwei Wang

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  17. Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration

    arXiv (Cornell University) · 2021-10-12

    Weichao Mao, Tamer Başar, Lin Forrest Yang, Kaiqing Zhang

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  18. Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction

    IEEE Transactions on Information Theory · 2021-10-15

    Gen Li, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen

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  19. Breaking the sample complexity barrier to regret-optimal model-free reinforcement learning

    Information and Inference A Journal of the IMA · 2022-12-17

    Gen Li, Laixi Shi, Yuxin Chen, Yuejie Chi

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  20. Predicting Potential Risk: Cerebral Stroke via Regret Minimization

    International Journal of Intelligent Systems · 2023-01-01

    Jie Zhang, Hao Chen, Cheng Jin, Qiangqiang He, Wei He, Chongjun Wang

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  21. Settling the sample complexity of model-based offline reinforcement learning

    The Annals of Statistics · 2024-02-01

    Gen Li, Laixi Shi, Yuxin Chen, Yuejie Chi, Yuting Wei

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  22. Cooperative Markov Decision Process model for human–machine co-adaptation in robot-assisted rehabilitation

    Knowledge-Based Systems · 2024-02-29

    Kairui Guo, Adrian Cheng, Yaqi Li, Jun Li, Rob Duffield, Steven Weidong Su

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  23. Sample Efficient Reinforcement Learning with Partial Dynamics Knowledge

    Proceedings of the AAAI Conference on Artificial Intelligence · 2024-03-24

    Meshal Alharbi, Mardavij Roozbehani, Munther A. Dahleh

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