Open Problem: Model Selection for Contextual Bandits

Dylan J. Foster
Dylan J. Foster

COLT, pp. 3842-3846, 2020.

Cited by: 0|Views39
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Abstract:

In statistical learning, algorithms for model selection allow the learner to adapt to the complexity of the best hypothesis class in a sequence. We ask whether similar guarantees are possible for contextual bandit learning.

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