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Heteroscedastic gaussian process regression

Le, Quoc; Smola, Alexander; Canu, Stephane

Description

This paper presents an algorithm to estimate simultaneously both mean and variance of a non parametric regression problem. The key point is that we are able to estimate variance locally unlike standard Gaussian Process regression or SVMs. This means that

CollectionsANU Research Publications
Date published: 2005
Type: Conference paper
URI: http://hdl.handle.net/1885/83170
Source: Proceedings of the 22nd International Conference on Machine Learning (ICML 2005)
DOI: 10.1145/1102351.1102413

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