Lipschitz Bandits: Regret Lower Bounds and Optimal Algorithms

19 May 2014

Papers citing "Lipschitz Bandits: Regret Lower Bounds and Optimal Algorithms"

10 / 10 papers shown

Title
Bandit Optimal Transport Lorenzo Croissant 102 0 0 11 Feb 2025
A Complete Characterization of Learnability for Stochastic Noisy Bandits Steve Hanneke Kun Wang 108 0 0 20 Jan 2025
Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning Subhojyoti Mukherjee Josiah P. Hanna Qiaomin Xie Robert Nowak 169 2 0 07 Jun 2024
Batched Stochastic Bandit for Nondegenerate Functions Yu Liu Yunlu Shu Tianyu Wang 115 0 0 09 May 2024
Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms Richard Combes Alexandre Proutiere 102 135 0 20 May 2014
Informational Confidence Bounds for Self-Normalized Averages and Applications Aurélien Garivier 52 44 0 13 Sep 2013
Kullback-Leibler upper confidence bounds for optimal sequential allocation Olivier Cappé Aurélien Garivier Odalric-Ambrym Maillard Rémi Munos Gilles Stoltz 93 394 0 03 Oct 2012
The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond Aurélien Garivier Olivier Cappé 133 613 0 12 Feb 2011
Contextual Bandits with Similarity Information Aleksandrs Slivkins 331 452 0 23 Jul 2009
Multi-Armed Bandits in Metric Spaces Robert D. Kleinberg Aleksandrs Slivkins E. Upfal 277 468 0 29 Sep 2008