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Corralling Stochastic Bandit Algorithms

Corralling Stochastic Bandit Algorithms

16 June 2020
R. Arora
T. V. Marinov
M. Mohri
ArXivPDFHTML

Papers citing "Corralling Stochastic Bandit Algorithms"

17 / 17 papers shown
Title
A Model Selection Approach for Corruption Robust Reinforcement Learning
A Model Selection Approach for Corruption Robust Reinforcement Learning
Chen-Yu Wei
Christoph Dann
Julian Zimmert
129
45
0
31 Dec 2024
Bias no more: high-probability data-dependent regret bounds for
  adversarial bandits and MDPs
Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPs
Chung-Wei Lee
Haipeng Luo
Chen-Yu Wei
Mengxiao Zhang
170
53
0
14 Jun 2020
Model Selection in Contextual Stochastic Bandit Problems
Model Selection in Contextual Stochastic Bandit Problems
Aldo Pacchiano
My Phan
Yasin Abbasi-Yadkori
Anup B. Rao
Julian Zimmert
Tor Lattimore
Csaba Szepesvári
166
94
0
03 Mar 2020
Model selection for contextual bandits
Model selection for contextual bandits
Dylan J. Foster
A. Krishnamurthy
Haipeng Luo
OffRL
164
90
0
03 Jun 2019
OSOM: A simultaneously optimal algorithm for multi-armed and linear
  contextual bandits
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
Beating Stochastic and Adversarial Semi-bandits Optimally and
  Simultaneously
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously
Julian Zimmert
Haipeng Luo
Chen-Yu Wei
193
81
0
25 Jan 2019
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits
Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits
Julian Zimmert
Yevgeny Seldin
AAML
161
179
0
19 Jul 2018
KL-UCB-switch: optimal regret bounds for stochastic bandits from both a
  distribution-dependent and a distribution-free viewpoints
KL-UCB-switch: optimal regret bounds for stochastic bandits from both a distribution-dependent and a distribution-free viewpoints
Aurélien Garivier
Hédi Hadiji
Pierre Menard
Gilles Stoltz
43
32
0
14 May 2018
More Adaptive Algorithms for Adversarial Bandits
More Adaptive Algorithms for Adversarial Bandits
Chen-Yu Wei
Haipeng Luo
126
182
0
10 Jan 2018
An Improved Parametrization and Analysis of the EXP3++ Algorithm for
  Stochastic and Adversarial Bandits
An Improved Parametrization and Analysis of the EXP3++ Algorithm for Stochastic and Adversarial Bandits
Yevgeny Seldin
Gábor Lugosi
69
92
0
20 Feb 2017
Corralling a Band of Bandit Algorithms
Corralling a Band of Bandit Algorithms
Alekh Agarwal
Haipeng Luo
Behnam Neyshabur
Robert Schapire
141
157
0
19 Dec 2016
Kernel-based methods for bandit convex optimization
Kernel-based methods for bandit convex optimization
Sébastien Bubeck
Ronen Eldan
Y. Lee
437
166
0
11 Jul 2016
An algorithm with nearly optimal pseudo-regret for both stochastic and
  adversarial bandits
An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits
P. Auer
Chao-Kai Chiang
69
111
0
27 May 2016
Explore First, Exploit Next: The True Shape of Regret in Bandit Problems
Explore First, Exploit Next: The True Shape of Regret in Bandit Problems
Aurélien Garivier
Pierre Ménard
Gilles Stoltz
46
213
0
23 Feb 2016
Deterministic MDPs with Adversarial Rewards and Bandit Feedback
Deterministic MDPs with Adversarial Rewards and Bandit Feedback
R. Arora
O. Dekel
Ambuj Tewari
77
31
0
16 Oct 2012
Bandits with heavy tail
Bandits with heavy tail
Sébastien Bubeck
Nicolò Cesa-Bianchi
Gábor Lugosi
184
290
0
08 Sep 2012
The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond
The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond
Aurélien Garivier
Olivier Cappé
166
612
0
12 Feb 2011
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