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  Support Vector methods in learning and feature extraction

Schölkopf, B., Smola, A., Müller, K.-R., Burges, C., & Vapnik, V. (1998). Support Vector methods in learning and feature extraction. In T. Downs, M. Frean, & M. Gallagher (Eds.), Ninth Australian Conference on Neural Networks (ACNN 1998) (pp. 72-78). St. Lucia.

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 Creators:
Schölkopf, B1, Author           
Smola, AJ, Author           
Müller, K-R, Author           
Burges, C, Author
Vapnik, V, Author           
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: The last years have witnessed an increasing interest in Support Vector (SV) machines, which use Mercer kernels for efficiently performing computations in high-dimensional spaces. In pattern recognition, the SV algorithm constructs nonlinear decision functions by training a classifier to perform a linear separation in some high-dimensional space which is nonlinearly related to input space. Recently, we have developed a technique for Nonlinear Principal Component Analysis (Kernel PCA) based on the same types of kernels. This way, we can for instance efficiently extract polynomial features of arbitrary order by computing projections onto principal components in the space of all products of n pixels of images. We explain the idea of Mercer kernels and associated feature spaces, and describe connections to the theory of reproducing kernels and to regularization theory, followed by an overview of the above algorithms employing these kernels.

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 Dates: 1998-02
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 1823
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Title: Ninth Australian Conference on Neural Networks (ACNN 1998)
Place of Event: Brisbane, Australia
Start-/End Date: 1998-02-11 - 1998-02-13

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Title: Ninth Australian Conference on Neural Networks (ACNN 1998)
Source Genre: Proceedings
 Creator(s):
Downs, T, Editor
Frean, M, Editor
Gallagher, M, Editor
Affiliations:
-
Publ. Info: St. Lucia
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 72 - 78 Identifier: ISBN: 1-86499-026-0