Consistency of Gaussian process regression in metric spaces
Gaussian process (GP) regressors are used in a wide variety of regression tasks, and many recent applications feature domains that are non-Euclidean manifolds or other metric spaces. In this paper, we examine formal consistency of GP regression on general metric spaces. Specifically, we consider a G...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Journal of Machine Learning Research
2021
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