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
Publication Date
December 1, 2008
Start / End Page
23 / 33
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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
Publication Date
December 1, 2008
Start / End Page
23 / 33