Optimization Over Zonotopes and Training Support Vector Machines

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dc.creatorBern, Marshall
dc.creatorEppstein, David
dc.date2001-05-08
dc.date.accessioned2026-07-07T03:17:08Z
dc.date.available2026-07-07T03:17:08Z
dc.descriptionWe make a connection between classical polytopes called zonotopes and Support Vector Machine (SVM) classifiers. We combine this connection with the ellipsoid method to give some new theoretical results on training SVMs. We also describe some special properties of soft margin C-SVMs as parameter C goes to infinity.
dc.descriptionTo appear in Workshop on Algorithms and Data Structures, 2001
dc.identifierhttps://arxiv.org/abs/cs/0105017
dc.identifierhttp://arxiv.org/abs/cs/0105017
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30610
dc.subjectComputational Geometry
dc.subjectArtificial Intelligence
dc.subjectF.2.2; G.1.6; I.2.6; I.5.1
dc.titleOptimization Over Zonotopes and Training Support Vector Machines
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