On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis

28 Jan 2019Kohei HayashiMasaaki ImaizumiYuichi Yoshida

In this paper, we study random subsampling of Gaussian process regression, one of the simplest approximation baselines, from a theoretical perspective. Although subsampling discards a large part of training data, we show provable guarantees on the accuracy of the predictive mean/variance and its generalization ability... (read more)

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