Robust Lipschitz Bandits to Adversarial Corruptions

29 May 2023

Papers citing "Robust Lipschitz Bandits to Adversarial Corruptions"

10 / 10 papers shown

Title
A Model Selection Approach for Corruption Robust Reinforcement Learning Chen-Yu Wei Christoph Dann Julian Zimmert 99 45 0 31 Dec 2024
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions Jiafan He Dongruo Zhou Tong Zhang Quanquan Gu 87 47 0 13 May 2022
Linear Contextual Bandits with Adversarial Corruptions Heyang Zhao Dongruo Zhou Quanquan Gu AAML 67 24 0 25 Oct 2021
Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms Qin Ding Yue Kang Yi-Wei Liu Thomas C. M. Lee Cho-Jui Hsieh James Sharpnack 68 8 0 05 Jun 2021
Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks Qin Ding Cho-Jui Hsieh James Sharpnack AAML 46 33 0 05 Jun 2021
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously Chung-Wei Lee Haipeng Luo Chen-Yu Wei Mengxiao Zhang Xiaojin Zhang 65 49 0 11 Feb 2021
Stochastic Linear Optimization with Adversarial Corruption Yingkai Li Edmund Y. Lou Liren Shan AAML 43 42 0 04 Sep 2019
Better Algorithms for Stochastic Bandits with Adversarial Corruptions Anupam Gupta Tomer Koren Kunal Talwar AAML 81 152 0 22 Feb 2019
Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit Yang Cao Zheng Wen Branislav Kveton Yao Xie 57 95 0 11 Feb 2018
Bandits and Experts in Metric Spaces Robert D. Kleinberg Aleksandrs Slivkins E. Upfal 136 125 0 04 Dec 2013