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Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit
  Feedback

Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback

21 January 2021
Marc Jourdan
Mojmír Mutný
Johannes Kirschner
Andreas Krause
ArXivPDFHTML

Papers citing "Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback"

6 / 6 papers shown
Title
On the Low-Complexity of Fair Learning for Combinatorial Multi-Armed Bandit
On the Low-Complexity of Fair Learning for Combinatorial Multi-Armed Bandit
Xiaoyi Wu
Bo Ji
Bin Li
FaML
53
0
0
01 Jan 2025
Efficient Planning in Combinatorial Action Spaces with Applications to
  Cooperative Multi-Agent Reinforcement Learning
Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning
Volodymyr Tkachuk
Seyed Alireza Bakhtiari
Johannes Kirschner
Matej Jusup
Ilija Bogunovic
Csaba Szepesvári
32
5
0
08 Feb 2023
Active Exploration via Experiment Design in Markov Chains
Active Exploration via Experiment Design in Markov Chains
Mojmír Mutný
Tadeusz Janik
Andreas Krause
46
14
0
29 Jun 2022
Top Two Algorithms Revisited
Top Two Algorithms Revisited
Marc Jourdan
Rémy Degenne
Dorian Baudry
R. D. Heide
E. Kaufmann
26
38
0
13 Jun 2022
Matroid Bandits: Fast Combinatorial Optimization with Learning
Matroid Bandits: Fast Combinatorial Optimization with Learning
Branislav Kveton
Zheng Wen
Azin Ashkan
Hoda Eydgahi
Brian Eriksson
46
119
0
20 Mar 2014
A Linearly Convergent Conditional Gradient Algorithm with Applications
  to Online and Stochastic Optimization
A Linearly Convergent Conditional Gradient Algorithm with Applications to Online and Stochastic Optimization
Dan Garber
Elad Hazan
66
96
0
20 Jan 2013
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