Data Centering in Feature Space
Abstract
This paper presents a family of methods for data translation in feature space, to be used in conjunction with kernel machines. The translations are performed using only kernel evaluations in input space. We use the methods to improve the numerical properties of kernel machines. Experiments with synthetic and real data demonstrate the effectiveness of data centering and highlight other interesting aspects of translation in feature space.
Cite
Text
Meilă. "Data Centering in Feature Space." Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003.Markdown
[Meilă. "Data Centering in Feature Space." Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003.](https://mlanthology.org/aistats/2003/meila2003aistats-data/)BibTeX
@inproceedings{meila2003aistats-data,
title = {{Data Centering in Feature Space}},
author = {Meilă, Marina},
booktitle = {Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics},
year = {2003},
pages = {209-216},
volume = {R4},
url = {https://mlanthology.org/aistats/2003/meila2003aistats-data/}
}