Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits

4 June 2020

Papers citing "Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits"

11 / 11 papers shown

Title
Model selection for contextual bandits Dylan J. Foster A. Krishnamurthy Haipeng Luo OffRL 161 90 0 03 Jun 2019
OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits Niladri S. Chatterji Vidya Muthukumar Peter L. Bartlett 51 44 0 24 May 2019
Semiparametric Contextual Bandits A. Krishnamurthy Zhiwei Steven Wu Vasilis Syrgkanis 112 44 0 12 Mar 2018
Small-loss bounds for online learning with partial information Thodoris Lykouris Karthik Sridharan Éva Tardos 75 41 0 09 Nov 2017
Misspecified Linear Bandits Avishek Ghosh Sayak Ray Chowdhury Aditya Gopalan 52 66 0 23 Apr 2017
Online Learning Without Prior Information Ashok Cutkosky K. Boahen ODL 34 74 0 07 Mar 2017
Corralling a Band of Bandit Algorithms Alekh Agarwal Haipeng Luo Behnam Neyshabur Robert Schapire 141 157 0 19 Dec 2016
Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning Francesco Orabona 132 103 0 15 Jun 2014
Minimax Optimal Algorithms for Unconstrained Linear Optimization H. B. McMahan 89 42 0 08 Feb 2013
Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit Alexandra Carpentier Rémi Munos 78 102 0 18 May 2012
Margin-adaptive model selection in statistical learning Sylvain Arlot Peter L. Bartlett 109 21 0 18 Apr 2008