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ข้อมูลเชิงลึก - Contextual Bandits with Graph Feedback
Stochastic Contextual Bandits with Graph Feedback: Regret Lower Bounds and Algorithms
The author establishes regret lower bounds for contextual bandits with graph feedback, introducing a graph-theoretical quantity to characterize the learning limit. Algorithms achieving near-optimal regrets are provided for different context sequences and feedback graphs.
Stochastic contextual bandits with graph feedback: Understanding the Fundamental Learning Limits
Contextual bandits with graph feedback present fundamental learning limits characterized by graph-theoretical quantities.
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