Ruprecht-Karls-Universität Heidelberg

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Forthcoming HCI Colloquia

 


29.05.2012

V.Franc (presenter) , A.Zien, B.Schoelkopf

Support Vector Machines as Probabilistic Models

Abstract:

We show how the SVM can be viewed as a maximum likelihood estimate of
a class of probabilistic models. This model class can be viewed as a
reparametrization of the SVM in a similar vein to the $\nu$-SVM
reparametrizing the classical ($C$-)SVM.
It is not discriminative, but has a non-uniform marginal. We illustrate
the benefits of this new view by re-deriving and re-investigating two
established SVM-related algorithms.

 

 

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