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Support vector machines in high-energy physics

Publication ,  Conference
Vossen, A
Published in: Inverted CERN School of Computing, iCSC 2005 and iCSC 2006 - Proceedings
December 1, 2008

This lecture introduces the support vector algorithms for classification and regression. They are an application of the so-called kernel trick, which allows the extension of a certain class of linear algorithms to the non-linear case. The kernel trick will be introduced and in the context of structural risk minimization, large margin algorithms for classification and regression will be presented. Current applications in high-energy physics will be discussed.

Duke Scholars

Published In

Inverted CERN School of Computing, iCSC 2005 and iCSC 2006 - Proceedings

ISBN

9789290833093

Publication Date

December 1, 2008

Start / End Page

23 / 33
 

Citation

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Vossen, A. (2008). Support vector machines in high-energy physics. In Inverted CERN School of Computing, iCSC 2005 and iCSC 2006 - Proceedings (pp. 23–33).
Vossen, A. “Support vector machines in high-energy physics.” In Inverted CERN School of Computing, ICSC 2005 and ICSC 2006 - Proceedings, 23–33, 2008.
Vossen A. Support vector machines in high-energy physics. In: Inverted CERN School of Computing, iCSC 2005 and iCSC 2006 - Proceedings. 2008. p. 23–33.
Vossen, A. “Support vector machines in high-energy physics.” Inverted CERN School of Computing, ICSC 2005 and ICSC 2006 - Proceedings, 2008, pp. 23–33.
Vossen A. Support vector machines in high-energy physics. Inverted CERN School of Computing, iCSC 2005 and iCSC 2006 - Proceedings. 2008. p. 23–33.

Published In

Inverted CERN School of Computing, iCSC 2005 and iCSC 2006 - Proceedings

ISBN

9789290833093

Publication Date

December 1, 2008

Start / End Page

23 / 33