Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic
and Adversarial Linear Bandits Simultaneously

Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously

11 February 2021

Papers citing "Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously"

17 / 17 papers shown

Title
Nearly Optimal Algorithms for Contextual Dueling Bandits from Adversarial Feedback Qiwei Di Jiafan He Quanquan Gu 29 1 0 16 Apr 2024
LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits Masahiro Kato Shinji Ito 36 0 0 05 Mar 2024
Best-of-Both-Worlds Linear Contextual Bandits Masahiro Kato Shinji Ito 53 0 0 27 Dec 2023
Robust Lipschitz Bandits to Adversarial Corruptions Yue Kang Cho-Jui Hsieh T. C. Lee AAML 30 8 0 29 May 2023
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond Christoph Dann Chen-Yu Wei Julian Zimmert 24 22 0 20 Feb 2023
Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes Chen Ye Wei Xiong Quanquan Gu Tong Zhang 31 29 0 12 Dec 2022
Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms Osama A. Hanna Lin F. Yang Christina Fragouli 27 11 0 08 Nov 2022
Best of Both Worlds Model Selection Aldo Pacchiano Christoph Dann Claudio Gentile 28 10 0 29 Jun 2022
Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds Shinji Ito Taira Tsuchiya Junya Honda AAML 23 16 0 14 Jun 2022
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs Shinji Ito Taira Tsuchiya Junya Honda 30 24 0 02 Jun 2022
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs Chloé Rouyer Dirk van der Hoeven Nicolò Cesa-Bianchi Yevgeny Seldin 21 15 0 01 Jun 2022
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions Jiafan He Dongruo Zhou Tong Zhang Quanquan Gu 66 46 0 13 May 2022
Linear Contextual Bandits with Adversarial Corruptions Heyang Zhao Dongruo Zhou Quanquan Gu AAML 28 24 0 25 Oct 2021
On Optimal Robustness to Adversarial Corruption in Online Decision Problems Shinji Ito 42 22 0 22 Sep 2021
Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptions Junyan Liu Shuai Li Dapeng Li 15 6 0 08 Jun 2021
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition Tiancheng Jin Longbo Huang Haipeng Luo 27 40 0 08 Jun 2021
Improved Corruption Robust Algorithms for Episodic Reinforcement Learning Yifang Chen S. Du Kevin G. Jamieson 24 22 0 13 Feb 2021