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...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2023-09-01
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Series: | Machine Learning with Applications |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827023000403 |