Bayesian Design Principles for Frequentist Sequential Learning

1 October 2023

Papers citing "Bayesian Design Principles for Frequentist Sequential Learning"

12 / 12 papers shown

Title
Decision Making in Hybrid Environments: A Model Aggregation Approach Haolin Liu Chen-Yu Wei Julian Zimmert 86 0 0 09 Feb 2025
Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability Fan Chen Dylan J. Foster Yanjun Han Jian Qian Alexander Rakhlin Yunbei Xu 46 1 0 07 Oct 2024
The Benefit of Being Bayesian in Online Conformal Prediction Zhiyu Zhang Zhou Lu Heng Yang 38 3 0 03 Oct 2024
Bayesian Design Principles for Offline-to-Online Reinforcement Learning Haotian Hu Yiqin Yang Jianing Ye Chengjie Wu Ziqing Mai Yujing Hu Tangjie Lv Changjie Fan Qianchuan Zhao Chongjie Zhang OffRL OnRL 50 3 0 31 May 2024
On Bits and Bandits: Quantifying the Regret-Information Trade-off Itai Shufaro Nadav Merlis Nir Weinberger Shie Mannor 40 0 0 26 May 2024
Provably Efficient Information-Directed Sampling Algorithms for Multi-Agent Reinforcement Learning Qiaosheng Zhang Chenjia Bai Shuyue Hu Zhen Wang Xuelong Li 44 1 0 30 Apr 2024
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm Miao Lu Han Zhong Tong Zhang Jose H. Blanchet OffRL OOD 79 6 0 04 Apr 2024
Optimistic Information Directed Sampling Gergely Neu Matteo Papini Ludovic Schwartz 55 2 0 23 Feb 2024
Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity Guhao Feng Han Zhong OffRL 76 2 0 28 Dec 2023
A Definition of Non-Stationary Bandits Yueyang Liu Kuang Xu Benjamin Van Roy 24 11 0 23 Feb 2023
Regret Bounds for Information-Directed Reinforcement Learning Botao Hao Tor Lattimore OffRL 52 17 0 09 Jun 2022
Kernel-based methods for bandit convex optimization Sébastien Bubeck Ronen Eldan Y. Lee 86 164 0 11 Jul 2016