Towards minimax policies for online linear optimization with bandit feedback

14 February 2012

Papers citing "Towards minimax policies for online linear optimization with bandit feedback"

27 / 27 papers shown

Title
Improved Regret of Linear Ensemble Sampling Harin Lee Min-hwan Oh 39 1 0 06 Nov 2024
Information-Theoretic Regret Bounds for Bandits with Fixed Expert Advice Khaled Eldowa Nicolò Cesa-Bianchi Alberto Maria Metelli Marcello Restelli 19 3 0 14 Mar 2023
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond Christoph Dann Chen-Yu Wei Julian Zimmert 26 22 0 20 Feb 2023
Refined Regret for Adversarial MDPs with Linear Function Approximation Yan Dai Haipeng Luo Chen-Yu Wei Julian Zimmert 31 12 0 30 Jan 2023
Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning Jiatai Huang Yan Dai Longbo Huang 27 6 0 25 Jan 2023
Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient Dylan J. Foster Noah Golowich Yanjun Han OffRL 33 29 0 19 Jan 2023
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization Le‐Yu Chen Jing Xu Luo Luo 36 15 0 16 Jan 2023
Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms Osama A. Hanna Lin F. Yang Christina Fragouli 27 11 0 08 Nov 2022
Socially Fair Reinforcement Learning Debmalya Mandal Jiarui Gan OffRL 30 13 0 26 Aug 2022
Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits Haipeng Luo Mengxiao Zhang Peng Zhao Zhi Zhou 34 17 0 12 Feb 2022
A bandit-learning approach to multifidelity approximation Yiming Xu Vahid Keshavarzzadeh Robert M. Kirby A. Narayan 16 6 0 29 Mar 2021
Linear Bandits on Uniformly Convex Sets Thomas Kerdreux Christophe Roux Alexandre d’Aspremont Sebastian Pokutta 31 7 0 10 Mar 2021
Unifying mirror descent and dual averaging A. Juditsky Joon Kwon Eric Moulines 17 29 0 30 Oct 2019
Adaptive Sampling for Stochastic Risk-Averse Learning Sebastian Curi Kfir Y. Levy Stefanie Jegelka Andreas Krause 24 52 0 28 Oct 2019
Regret Bounds for Batched Bandits Hossein Esfandiari Amin Karbasi Abbas Mehrabian Vahab Mirrokni 28 61 0 11 Oct 2019
Bandit Convex Optimization in Non-stationary Environments Peng Zhao G. Wang Lijun Zhang Zhi Zhou 36 41 0 29 Jul 2019
Exploration by Optimisation in Partial Monitoring Tor Lattimore Csaba Szepesvári 33 38 0 12 Jul 2019
Semiparametric Contextual Bandits A. Krishnamurthy Zhiwei Steven Wu Vasilis Syrgkanis 33 44 0 12 Mar 2018
Online Learning: A Comprehensive Survey Guosheng Lin Doyen Sahoo Jing Lu P. Zhao OffRL 31 634 0 08 Feb 2018
The Price of Differential Privacy For Online Learning Naman Agarwal Karan Singh FedML 14 94 0 27 Jan 2017
Corralling a Band of Bandit Algorithms Alekh Agarwal Haipeng Luo Behnam Neyshabur Robert Schapire 30 154 0 19 Dec 2016
Explore no more: Improved high-probability regret bounds for non-stochastic bandits Gergely Neu 22 181 0 10 Jun 2015
The entropic barrier: a simple and optimal universal self-concordant barrier Sébastien Bubeck Ronen Eldan 26 65 0 04 Dec 2014
On the Complexity of Bandit Linear Optimization Ohad Shamir 37 14 0 11 Aug 2014
Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms Wei Chen Yajun Wang Yang Yuan Qinshi Wang 54 279 0 31 Jul 2014
On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization Ohad Shamir 41 190 0 11 Sep 2012
Contextual Bandits with Similarity Information Aleksandrs Slivkins 51 451 0 23 Jul 2009