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LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual
  Bandits

LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits

5 March 2024
Masahiro Kato
Shinji Ito
ArXivPDFHTML

Papers citing "LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits"

3 / 3 papers shown
Title
Best-of-three-worlds Analysis for Linear Bandits with
  Follow-the-regularized-leader Algorithm
Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm
Fang-yuan Kong
Canzhe Zhao
Shuai Li
27
11
0
13 Mar 2023
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial
  Corruptions
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions
Jiafan He
Dongruo Zhou
Tong Zhang
Quanquan Gu
61
46
0
13 May 2022
Regret Lower Bound and Optimal Algorithm for High-Dimensional Contextual
  Linear Bandit
Regret Lower Bound and Optimal Algorithm for High-Dimensional Contextual Linear Bandit
Ke Li
Yun Yang
N. Narisetty
18
7
0
23 Sep 2021
1