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
2008-01-01
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.
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