@inproceedings{42e55ed765a448a7a6f637bb9188de62,
title = "Selecting from an infinite set of features in SVM",
abstract = "Dealing with the continuous parameters of a feature extraction method has always been a difficult task that is usually solved by cross-validation. In this paper, we propose an active set algorithm for selecting automatically these parameters in a SVM classification context. Our experiments on texture recognition and BCI signal classification show that optimizing the feature parameters in a continuous space while learning the decision function yields to better performances than using fixed parameters obtained from a grid sampling.",
author = "R{\'e}mi Flamary and Florian Yger and Alain Rakotomamonjy",
note = "Publisher Copyright: {\textcopyright} European Symposium on Artificial Neural Networks. All rights reserved.; 19th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2011 ; Conference date: 27-04-2011 Through 29-04-2011",
year = "2011",
month = jan,
day = "1",
language = "English",
series = "ESANN 2011 - 19th European Symposium on Artificial Neural Networks",
publisher = "ESANN (i6doc.com)",
pages = "327--332",
booktitle = "Proceedings of the 19th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, ESANN 2011",
}