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Jul, 2021
高斯过程自适应诱导点选择
Adaptive Inducing Points Selection For Gaussian Processes
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Théo Galy-Fajou, Manfred Opper
TL;DR
这篇研究论文介绍了一种在线学习高斯过程（Gaussian Processes）的方法，其中采用了有效的变分方法并使用了稀疏技术来降低观测数据的数量，并对inducing points进行自适应添加，从而提高算法的性能。
Abstract
gaussian processes
(\textbf{GPs}) are flexible
non-parametric models
with strong probabilistic interpretation. While being a standard choice for performing inference on time series, GPs have few techniques to wor
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