BriefGPT.xyz
Jun, 2020
利用稀疏高斯过程模型实现可扩展的汤普森抽样
Scalable Thompson Sampling using Sparse Gaussian Process Models
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Sattar Vakili, Victor Picheny, Artem Artemev
TL;DR
本文提出了一种基于稀疏高斯过程模型实现的可扩展Thompson抽样算法,通过理论证明和实验验证表明该算法不会损失标准Thompson抽样算法的遗憾性能,并成功地应用于高通量分子设计任务等实际问题。
Abstract
thompson sampling
(TS) with
gaussian process
(GP) models is a powerful tool for optimizing non-convex objective functions. Despite favourable theoretical properties, the computational complexity of the standard a
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