Design of Experiments for Stochastic Contextual Linear Bandits

21 July 2021

Papers citing "Design of Experiments for Stochastic Contextual Linear Bandits"

9 / 9 papers shown

Title
Active Few-Shot Fine-Tuning Jonas Hübotter Bhavya Sukhija Lenart Treven Yarden As Andreas Krause 48 1 0 13 Feb 2024
Concentrated Differential Privacy for Bandits Achraf Azize D. Basu 33 4 0 01 Sep 2023
Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data Ruiqi Zhang Andrea Zanette OffRL OnRL 42 7 0 10 Jul 2023
Estimating Optimal Policy Value in General Linear Contextual Bandits Jonathan Lee Weihao Kong Aldo Pacchiano Vidya Muthukumar Emma Brunskill 30 0 0 19 Feb 2023
Multi-task Representation Learning for Pure Exploration in Linear Bandits Yihan Du Longbo Huang Wen Sun 27 4 0 09 Feb 2023
Anonymous Bandits for Multi-User Systems Hossein Esfandiari Vahab Mirrokni Jon Schneider PICV 26 0 0 21 Oct 2022
Safe Exploration for Efficient Policy Evaluation and Comparison Runzhe Wan Branislav Kveton Rui Song OffRL 36 10 0 26 Feb 2022
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 122 167 0 06 Jan 2021
Reward-Free Exploration for Reinforcement Learning Chi Jin A. Krishnamurthy Max Simchowitz Tiancheng Yu OffRL 112 194 0 07 Feb 2020