Rectangularization of Gaussian process regression for optimization of hyperparameters

Gaussian process regression (GPR) is a powerful machine learning method which has recently enjoyed wider use, in particular in physical sciences. In its original formulation, GPR uses a square matrix of covariances among training data and can be viewed as linear regression problem with equal numbers...

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Bibliographic Details

Published in:	Machine Learning with Applications
Main Authors:	Sergei Manzhos, Manabu Ihara
Format:	Article
Language:	English
Published:	Elsevier 2023-09-01
Subjects:	Gaussian process regression Hyperparameter optimization Rectangular matrix
Online Access:	http://www.sciencedirect.com/science/article/pii/S2666827023000403