Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits

2 September 2023

Papers citing "Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits"

7 / 7 papers shown

Title
A Model Selection Approach for Corruption Robust Reinforcement Learning Chen-Yu Wei Christoph Dann Julian Zimmert 80 44 0 31 Dec 2024
LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits Masahiro Kato Shinji Ito 34 0 0 05 Mar 2024
Refined Sample Complexity for Markov Games with Independent Linear Function Approximation Yan Dai Qiwen Cui S. S. Du 35 1 0 11 Feb 2024
Best-of-Both-Worlds Linear Contextual Bandits Masahiro Kato Shinji Ito 38 0 0 27 Dec 2023
First- and Second-Order Bounds for Adversarial Linear Contextual Bandits Julia Olkhovskaya J. Mayo T. Erven Gergely Neu Chen-Yu Wei 51 10 0 01 May 2023
Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States Julian Zimmert Naman Agarwal Satyen Kale 24 17 0 06 Feb 2022
Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds E. Emamjomeh-Zadeh Chen-Yu Wei Haipeng Luo David Kempe 24 5 0 07 Mar 2020