ML Anthology

Heteroscedastic Gaussian Process Regression

Quoc V. Le, Alexander J. Smola, Stéphane Canu
ICML 2005 pp. 489-496
doi:10.1145/1102351.1102413 /icml/2005/le2005icml-heteroscedastic/

Abstract

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

PDF ICML Semantic Scholar

Cite

Text

Le et al. "Heteroscedastic Gaussian Process Regression." International Conference on Machine Learning, 2005. doi:10.1145/1102351.1102413

Markdown

[Le et al. "Heteroscedastic Gaussian Process Regression." International Conference on Machine Learning, 2005.](https://mlanthology.org/icml/2005/le2005icml-heteroscedastic/) doi:10.1145/1102351.1102413

BibTeX

@inproceedings{le2005icml-heteroscedastic,
  title     = {{Heteroscedastic Gaussian Process Regression}},
  author    = {Le, Quoc V. and Smola, Alexander J. and Canu, Stéphane},
  booktitle = {International Conference on Machine Learning},
  year      = {2005},
  pages     = {489-496},
  doi       = {10.1145/1102351.1102413},
  url       = {https://mlanthology.org/icml/2005/le2005icml-heteroscedastic/}
}