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...
| 出版年: | Machine Learning with Applications |
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| 主要な著者: | , |
| フォーマット: | 論文 |
| 言語: | 英語 |
| 出版事項: |
Elsevier
2023-09-01
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| 主題: | |
| オンライン･アクセス: | http://www.sciencedirect.com/science/article/pii/S2666827023000403 |