We review the role played by non-smooth optimization techniques in many recent applications in classification area. Starting from the classical concept of linear separability in binary classification, we recall the more general concepts of polyhedral, ellipsoidal and max-min separability. Finally we focus our attention on the support vector machine (SVM) approach and on the more recent transductive SVM technique.

Non-smoothness in classification problems

GORGONE, ENRICO
2008

Abstract

We review the role played by non-smooth optimization techniques in many recent applications in classification area. Starting from the classical concept of linear separability in binary classification, we recall the more general concepts of polyhedral, ellipsoidal and max-min separability. Finally we focus our attention on the support vector machine (SVM) approach and on the more recent transductive SVM technique.
Classification; Non-smooth optimization; Separation of sets; Software; Control and Optimization; Applied Mathematics
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11584/212586
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