Kernel classifier with Correntropy loss

Abstract

Classification can be seen as a mapping problem where some function of xn predicts the expectation of a class variable yn. This paper uses kernel methods for the prediction of class variable, together with a recently proposed cost function for classification, called Correntropy-loss (C-loss) function. C-Loss is a non-convex loss function based on a… (More)
DOI: 10.1109/IJCNN.2012.6252721

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