Adapting multi-armed bandits policies to contextual bandits scenarios

11 Nov 2018 David Cortes

This work explores adaptations of successful multi-armed bandits policies to the online contextual bandits scenario with binary rewards using binary classification algorithms such as logistic regression as black-box oracles. Some of these adaptations are achieved through bootstrapping or approximate bootstrapping, while others rely on other forms of randomness, resulting in more scalable approaches than previous works, and the ability to work with any type of classification algorithm... (read more)

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METHOD TYPE
Logistic Regression
Generalized Linear Models