A Change-Detection Based Thompson Sampling Framework for Non-Stationary Bandits

6 September 2020

Papers citing "A Change-Detection Based Thompson Sampling Framework for Non-Stationary Bandits"

10 / 10 papers shown

Title
Deep Learning Predictive Band Switching in Wireless Networks Faris B. Mismar Ahmad Alammouri Ahmed Alkhateeb J. Andrews B. Evans 21 25 0 02 Oct 2019
Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit Yang Cao Zheng Wen Branislav Kveton Yao Xie 57 95 0 11 Feb 2018
A Change-Detection based Framework for Piecewise-stationary Multi-Armed Bandit Problem Fang Liu Joohyung Lee Ness B. Shroff 54 116 0 08 Nov 2017
Taming Non-stationary Bandits: A Bayesian Approach Vishnu Raj Sheetal Kalyani 107 76 0 31 Jul 2017
Reward Maximization Under Uncertainty: Leveraging Side-Observations on Networks Swapna Buccapatnam Fang Liu A. Eryilmaz Ness B. Shroff 48 28 0 26 Apr 2017
Collaborative Filtering Bandits Shuai Li Alexandros Karatzoglou Claudio Gentile 74 315 0 11 Feb 2015
Optimal Exploration-Exploitation in a Multi-Armed-Bandit Problem with Non-stationary Rewards Omar Besbes Y. Gur A. Zeevi 66 127 0 13 May 2014
Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration E. Contal David Buffoni Alexandre Robicquet Nicolas Vayatis 58 213 0 19 Apr 2013
Thompson Sampling in Switching Environments with Bayesian Online Change Point Detection J. Mellor J. Shapiro 79 40 0 15 Feb 2013
On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems Aurélien Garivier Eric Moulines 84 295 0 22 May 2008