Cawley et al., 2004 - Google Patents
Heteroscedastic kernel ridge regressionCawley et al., 2004
View PDF- Document ID
- 14431587079407386612
- Author
- Cawley G
- Talbot N
- Foxall R
- Dorling S
- Mandic D
- Publication year
- Publication venue
- Neurocomputing
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Snippet
In this paper we extend a form of kernel ridge regression (KRR) for data characterised by a heteroscedastic (ie input dependent variance) Gaussian noise process, introduced in Foxall et al.(in: Proceedings of the European Symposium on Artificial Neural Networks (ESANN …
- 238000000034 method 0 abstract description 27
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- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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