Taming Non-stationary Bandits: A Bayesian Approach

Taming Non-stationary Bandits: A Bayesian Approach

31 July 2017

Sheetal Kalyani

Papers citing "Taming Non-stationary Bandits: A Bayesian Approach"

9 / 9 papers shown

Title
Bridging Rested and Restless Bandits with Graph-Triggering: Rising and Rotting Gianmarco Genalti Marco Mussi Nicola Gatti Marcello Restelli Matteo Castiglioni Alberto Maria Metelli 22 0 0 09 Sep 2024
Non-Stationary Latent Auto-Regressive Bandits Anna L. Trella Walter Dempsey Asim H. Gazi Ziping Xu Finale Doshi-Velez Susan A. Murphy 14 1 0 05 Feb 2024
Continual Learning as Computationally Constrained Reinforcement Learning Saurabh Kumar Henrik Marklund Anand Srinivasa Rao Yifan Zhu Hong Jun Jeon Yueyang Liu Benjamin Van Roy CLL 22 21 0 10 Jul 2023
Discounted Thompson Sampling for Non-Stationary Bandit Problems Han Qi Yue Wang Li Zhu 19 4 0 18 May 2023
SLOPT: Bandit Optimization Framework for Mutation-Based Fuzzing Yuki Koike H. Katsura Hiromu Yakura Yuma Kurogome 10 5 0 07 Nov 2022
Safety Aware Changepoint Detection for Piecewise i.i.d. Bandits Subhojyoti Mukherjee 9 1 0 27 May 2022
An empirical evaluation of active inference in multi-armed bandits D. Marković Hrvoje Stojić Sarah Schwöbel S. Kiebel 20 34 0 21 Jan 2021
A Change-Detection Based Thompson Sampling Framework for Non-Stationary Bandits Gourab Ghatak 8 17 0 06 Sep 2020
Weighted Linear Bandits for Non-Stationary Environments Yoan Russac Claire Vernade Olivier Cappé 75 100 0 19 Sep 2019