Updates for Nonlinear Discriminants
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 660-664.
Abstract
A novel training algorithm for nonlinear discriminants for classification and regression in Reproducing Kernel Hilbert Spaces (RKHSs) is presented. It is shown how the overdetermined linear least-squares-problem in the corresponding RKHS may be solved within a greedy forward selection scheme by updating the pseudoinverse in an order-recursive way. The described construction of the pseudoinverse gives rise to an update of the orthogonal decomposition of the reduced Gram matrix in linear time. Regularization in the spirit of Ridge regression may then easily be applied in the orthogonal space. Various experiments for both classification and regression are performed to show the competitiveness of the proposed method.
@inproceedings{ijcai2007p105,
title = {Updates for Nonlinear Discriminants},
author = {Andelic, Edin and Schafföner, Martin and Katz, Marcel and Krüger, Sven E. and Wendemuth, Andreas},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {660--664},
year = {2007},
url = {https://ijcai.org/proceedings/2007/105},
}
TY - CPAPER TI - Updates for Nonlinear Discriminants AU - Andelic, Edin AU - Schafföner, Martin AU - Katz, Marcel AU - Krüger, Sven E. AU - Wendemuth, Andreas T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 660 EP - 664 UR - https://ijcai.org/proceedings/2007/105 ER -Copied
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