Performance analysis for L\_2 kernel classification

NeurIPS 2008 Jooseuk KimClayton Scott

We provide statistical performance guarantees for a recently introduced kernel classifier that optimizes the $L_2$ or integrated squared error (ISE) of a difference of densities. The classifier is similar to a support vector machine (SVM) in that it is the solution of a quadratic program and yields a sparse classifier... (read more)

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