Recovering Bandits

31 October 2019

Papers citing "Recovering Bandits"

14 / 14 papers shown

Title
Preferences Evolve And So Should Your Bandits: Bandits with Evolving States for Online Platforms Khashayar Khosravi R. Leme Chara Podimata Apostolis Tsorvantzis 69 0 0 21 Jul 2023
Discrepancy-Based Algorithms for Non-Stationary Rested Bandits Corinna Cortes Giulia DeSalvo Vitaly Kuznetsov M. Mohri Scott Yang 109 19 0 29 Oct 2017
Taming Non-stationary Bandits: A Bayesian Approach Vishnu Raj Sheetal Kalyani 112 76 0 31 Jul 2017
Non-Stationary Bandits with Habituation and Recovery Dynamics Yonatan Dov Mintz A. Aswani Philip M. Kaminsky E. Flowers Yoshimi Fukuoka 186 57 0 26 Jul 2017
Minimax Regret Bounds for Reinforcement Learning M. G. Azar Ian Osband Rémi Munos 92 778 0 16 Mar 2017
Rotting Bandits Nir Levine K. Crammer Shie Mannor 56 102 0 23 Feb 2017
Time-Varying Gaussian Process Bandit Optimization Ilija Bogunovic Jonathan Scarlett Volkan Cevher 111 98 0 25 Jan 2016
Multi-armed Bandit Problem with Known Trend Djallel Bouneffouf Raphael Feraud 37 83 0 28 Aug 2015
(More) Efficient Reinforcement Learning via Posterior Sampling Ian Osband Daniel Russo Benjamin Van Roy 137 535 0 04 Jun 2013
Learning to Optimize Via Posterior Sampling Daniel Russo Benjamin Van Roy 206 703 0 11 Jan 2013
Kullback-Leibler upper confidence bounds for optimal sequential allocation Olivier Cappé Aurélien Garivier Odalric-Ambrym Maillard Rémi Munos Gilles Stoltz 129 395 0 03 Oct 2012
Thompson Sampling for Contextual Bandits with Linear Payoffs Shipra Agrawal Navin Goyal 204 1,006 0 15 Sep 2012
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design Niranjan Srinivas Andreas Krause Sham Kakade Matthias Seeger 154 1,624 0 21 Dec 2009
On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems Aurélien Garivier Eric Moulines 97 294 0 22 May 2008