Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits

1 June 2016

Papers citing "Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits"

6 / 6 papers shown

Title
LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits Masahiro Kato Shinji Ito 90 0 0 05 Mar 2024
Taking a hint: How to leverage loss predictors in contextual bandits? Chen-Yu Wei Haipeng Luo Alekh Agarwal 82 27 0 04 Mar 2020
Efficient Algorithms for Adversarial Contextual Learning Vasilis Syrgkanis A. Krishnamurthy Robert Schapire 87 79 0 08 Feb 2016
BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits Alexander Rakhlin Karthik Sridharan OffRL 182 72 0 06 Feb 2016
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits Alekh Agarwal Daniel J. Hsu Satyen Kale John Langford Lihong Li Robert Schapire OffRL 213 504 0 04 Feb 2014
Efficient Optimal Learning for Contextual Bandits Miroslav Dudík Daniel J. Hsu Satyen Kale Nikos Karampatziakis John Langford L. Reyzin Tong Zhang 132 300 0 13 Jun 2011