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Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits
  with Linear Payoff Functions
v1v2 (latest)

Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions

AAAI Conference on Artificial Intelligence (AAAI), 2021
20 January 2021
Kei Takemura
Shinji Ito
Daisuke Hatano
Hanna Sumita
Takuro Fukunaga
Naonori Kakimura
Ken-ichi Kawarabayashi
ArXiv (abs)PDFHTMLGithub

Papers citing "Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions"

3 / 3 papers shown
Efficient Best-of-Both-Worlds Algorithms for Contextual Combinatorial Semi-Bandits
Efficient Best-of-Both-Worlds Algorithms for Contextual Combinatorial Semi-Bandits
Mengmeng Li
Philipp Schneider
Jelisaveta Aleksić
Daniel Kuhn
129
1
0
26 Aug 2025
Effective Off-Policy Evaluation and Learning in Contextual Combinatorial
  Bandits
Effective Off-Policy Evaluation and Learning in Contextual Combinatorial BanditsACM Conference on Recommender Systems (RecSys), 2024
Tatsuhiro Shimizu
Koichi Tanaka
Ren Kishimoto
Haruka Kiyohara
Masahiro Nomura
Yuta Saito
CMLOffRL
369
9
0
20 Aug 2024
Contextual Combinatorial Bandits with Probabilistically Triggered Arms
Contextual Combinatorial Bandits with Probabilistically Triggered ArmsInternational Conference on Machine Learning (ICML), 2023
Xutong Liu
Jinhang Zuo
Siwei Wang
John C. S. Lui
Mohammad Hajiesmaili
Adam Wierman
Wei Chen
205
26
0
30 Mar 2023
1
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