Regret Bounds for Batched Bandits

11 October 2019

Vahab Mirrokni

Papers citing "Regret Bounds for Batched Bandits"

40 / 40 papers shown

Title
Batched Nonparametric Bandits via k-Nearest Neighbor UCB Sakshi Arya OffRL 25 0 0 15 May 2025
A Near-optimal, Scalable and Corruption-tolerant Framework for Stochastic Bandits: From Single-Agent to Multi-Agent and Beyond Zicheng Hu Cheng Chen 72 0 0 11 Feb 2025
Adversarial Online Learning with Temporal Feedback Graphs Khashayar Gatmiry Jon Schneider 23 0 0 30 Jun 2024
Optimal Batched Linear Bandits Xuanfei Ren Tianyuan Jin Pan Xu 40 2 0 06 Jun 2024
A Batch Sequential Halving Algorithm without Performance Degradation Sotetsu Koyamada Soichiro Nishimori Shin Ishii 32 0 0 01 Jun 2024
Batched Stochastic Bandit for Nondegenerate Functions Yu Liu Yunlu Shu Tianyu Wang 52 0 0 09 May 2024
Replicability is Asymptotically Free in Multi-armed Bandits Junpei Komiyama Shinji Ito Yuichi Yoshida Souta Koshino 35 1 0 12 Feb 2024
Falcon: Fair Active Learning using Multi-armed Bandits Ki Hyun Tae Hantian Zhang Jaeyoung Park Kexin Rong Steven Euijong Whang FaML 14 2 0 23 Jan 2024
Experiment Planning with Function Approximation Aldo Pacchiano Jonathan Lee Emma Brunskill OffRL 37 3 0 10 Jan 2024
Best Arm Identification in Batched Multi-armed Bandit Problems Sheng Cao Simai He Ruoqing Jiang Jin Xu Hongsong Yuan 15 1 0 21 Dec 2023
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity Emmeran Johnson Ciara Pike-Burke Patrick Rebeschini OffRL 29 2 0 02 Oct 2023
Cooperative Multi-agent Bandits: Distributed Algorithms with Optimal Individual Regret and Constant Communication Costs L. Yang Xuchuang Wang Mohammad Hajiesmaili Lijun Zhang John C. S. Lui Don Towsley 38 5 0 08 Aug 2023
Preferences Evolve And So Should Your Bandits: Bandits with Evolving States for Online Platforms Khashayar Khosravi R. Leme Chara Podimata Apostolis Tsorvantzis 26 0 0 21 Jul 2023
Robust and differentially private stochastic linear bandits Vasileios Charisopoulos Hossein Esfandiari Vahab Mirrokni FedML 29 1 0 23 Apr 2023
Adaptive Experimentation at Scale: A Computational Framework for Flexible Batches Ethan Che Hongseok Namkoong OffRL 51 1 0 21 Mar 2023
A Lipschitz Bandits Approach for Continuous Hyperparameter Optimization Yasong Feng Weijian Luo Yimin Huang Tianyu Wang 26 8 0 03 Feb 2023
Anonymous Bandits for Multi-User Systems Hossein Esfandiari Vahab Mirrokni Jon Schneider PICV 26 0 0 21 Oct 2022
Reward Imputation with Sketching for Contextual Batched Bandits Xiao Zhang Ninglu Shao Zihua Si Jun Xu Wen Wang Hanjing Su Jirong Wen OffRL 25 1 0 13 Oct 2022
Replicable Bandits Hossein Esfandiari Alkis Kalavasis Amin Karbasi Andreas Krause Vahab Mirrokni Grigoris Velegkas 37 14 0 04 Oct 2022
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation Dan Qiao Yu Wang OffRL 75 13 0 03 Oct 2022
An Asymptotically Optimal Batched Algorithm for the Dueling Bandit Problem Arpit Agarwal R. Ghuge V. Nagarajan 25 1 0 25 Sep 2022
Differentially Private Stochastic Linear Bandits: (Almost) for Free Osama A. Hanna Antonious M. Girgis Christina Fragouli Suhas Diggavi FedML 29 18 0 07 Jul 2022
Better Best of Both Worlds Bounds for Bandits with Switching Costs I Zaghloul Amir Guy Azov Tomer Koren Roi Livni 15 14 0 07 Jun 2022
Batched Dueling Bandits Arpit Agarwal R. Ghuge V. Nagarajan 120 10 0 22 Feb 2022
Synthetically Controlled Bandits Vivek Farias C. Moallemi Tianyi Peng Andrew Zheng 33 13 0 14 Feb 2022
The Impact of Batch Learning in Stochastic Linear Bandits Danil Provodin Pratik Gajane Mykola Pechenizkiy M. Kaptein 16 2 0 14 Feb 2022
Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality Jiawei Huang Jinglin Chen Li Zhao Tao Qin Nan Jiang Tie-Yan Liu OffRL 35 24 0 14 Feb 2022
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost Dan Qiao Ming Yin Ming Min Yu Wang 43 28 0 13 Feb 2022
Solving Multi-Arm Bandit Using a Few Bits of Communication Osama A. Hanna Lin F. Yang Christina Fragouli 26 16 0 11 Nov 2021
The Impact of Batch Learning in Stochastic Bandits Danil Provodin Pratik Gajane Mykola Pechenizkiy M. Kaptein OffRL 22 2 0 03 Nov 2021
Lipschitz Bandits with Batched Feedback Yasong Feng Zengfeng Huang Tianyu Wang 16 14 0 19 Oct 2021
Gaussian Process Bandit Optimization with Few Batches Zihan Li Jonathan Scarlett GP 135 47 0 15 Oct 2021
Batched Thompson Sampling Cem Kalkanli Ayfer Özgür OffRL 51 19 0 01 Oct 2021
Design of Experiments for Stochastic Contextual Linear Bandits Andrea Zanette Kefan Dong Jonathan Lee Emma Brunskill OffRL 32 17 0 21 Jul 2021
Differentially Private Multi-Armed Bandits in the Shuffle Model J. Tenenbaum Haim Kaplan Yishay Mansour Uri Stemmer FedML 19 28 0 05 Jun 2021
Parallelizing Thompson Sampling Amin Karbasi Vahab Mirrokni M. Shadravan 56 23 0 02 Jun 2021
An Algorithm for Stochastic and Adversarial Bandits with Switching Costs Chloé Rouyer Yevgeny Seldin Nicolò Cesa-Bianchi AAML 21 24 0 19 Feb 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 122 167 0 06 Jan 2021
Linear Bandits with Limited Adaptivity and Learning Distributional Optimal Design Yufei Ruan Jiaqi Yang Yuanshuo Zhou OffRL 102 51 0 04 Jul 2020
Maximal Objectives in the Multi-armed Bandit with Applications Eren Ozbay Vijay Kamble 35 0 0 11 Jun 2020