Gaussian Process Regression Based on Toeplitz Computation of O ( N 2 ) Operations and O ( N ) - level Storage

Abstract

Gaussian process (GP) regression is a Bayesian nonparametric model showing good performance in various applications. However, its hyperparameter-estimating procedure may contain numerous matrix manipulations of O(N) arithmetic operations, in addition to the O(N)-level storage. Motivated by handling the real-world large dataset of 24000 wind-turbine data, we… (More)

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