Ensemble Sampling
Xiuyuan Lu · Benjamin Van Roy

Wed Dec 6th 06:30 -- 10:30 PM @ Pacific Ballroom #20 #None

Thompson sampling has emerged as an effective heuristic for a broad range of online decision problems. In its basic form, the algorithm requires computing and sampling from a posterior distribution over models, which is tractable only for simple special cases. This paper develops ensemble sampling, which aims to approximate Thompson sampling while maintaining tractability even in the face of complex models such as neural networks. Ensemble sampling dramatically expands on the range of applications for which Thompson sampling is viable. We establish a theoretical basis that supports the approach and present computational results that offer further insight.

Author Information

Xiuyuan Lu (Stanford University)
Benjamin Van Roy (Stanford University)

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