Functional Bandits

Long Tran-Thanh; Jia Yuan Yu

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arXiv · 1405.2432

Functional Bandits

Long Tran-Thanh·Jia Yuan Yu

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Abstract

We introduce the functional bandit problem, where the objective is to find an arm that optimises a known functional of the unknown arm-reward distributions. These problems arise in many settings such as maximum entropy methods in natural language processing, and risk-averse decision-making, but current best-arm identification techniques fail in these domains. We propose a new approach, that combines functional estimation and arm elimination, to tackle this problem. This method achieves provably efficient performance guarantees. In addition, we illustrate this method on a number of important functionals in risk management and information theory, and refine our generic theoretical results in those cases.

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Long Tran-Thanh, Jia Yuan Yu. 2014-05-10. Functional Bandits. https://arxiv.org/abs/1405.2432

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