Efficient Contextual Bandits with Continuous Actions
arXiv:2006.06040
Abstract
We create a computationally tractable algorithm for contextual bandits with continuous actions having unknown structure. Our reduction-style algorithm composes with most supervised learning representations. We prove that it works in a general sense and verify the new functionality with large-scale experiments.
arXiv commentTo appear at NeurIPS 2020
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