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A Parameter-Free Algorithm for Misspecified Linear ...
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由 K Takemura 著作2021被引用 21 次 — This is the first algorithm that guarantees a high-probability regret bound for the MLCB problem without knowledge of the approximation parameter ε.
A Parameter-Free Algorithm for Misspecified Linear ...
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由 K Takemura 著作2021被引用 21 次 — We investigate the misspecified linear con- textual bandit (MLCB) problem, which is a generalization of the linear contextual ban- dit (LCB) problem.
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A Parameter-Free Algorithm for Misspecified Linear ...
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2021年4月14日 — We investigate the misspecified linear contextual bandit (MLCB) problem, which is a generalization of the linear contextual bandit (LCB) problem ...
A Parameter-Free Algorithm for Misspecified Linear ...
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A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits. Kei ... Abstract: We investigate the misspecified linear contextual bandit (MLCB) ...
Shinji Ito
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Parameter-Free Multi-Armed Bandit Algorithms with Hybrid Data-Dependent Regret Bounds ... A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits. K ...
Dealing With Misspecification In Fixed-Confidence Linear ...
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由 C Réda 著作2021被引用 14 次 — (3) We design the first algorithm for Top-m identification in misspecified linear bandits. We derive an upper bound to its sample complexity ...
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Robust Contextual Linear Bandits
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2023年7月16日 — Takemura, Ito, Hatano et al. (2021) 'A Parameter Free Algorithm for Misspecified Linear Contextual Bandits' AISTATS. Dong and Yang (2023) ...
Shinji Ito
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Parameter-Free Multi-Armed Bandit Algorithms with Hybrid Data-Dependent Regret Bounds ... A parameter-free algorithm for misspecified linear contextual bandits.
Multi-Agent Learning with Heterogeneous Linear ...
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由 A Do 著作2023 — A parameter-free algorithm for misspecified linear contextual bandits. In. International Conference on Artificial Intelligence and Statistics, pages 3367 ...
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Robust Contextual Linear Bandits
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Takemura et al. (2021) proposed the first algorithm for the misspecified linear contextual bandit problem without knowledge of the approximation parameter. This ...
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