An ADMM Solver for the MKL-L_0/1-SVM

03/08/2023

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by   Yijie Shi, et al.

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We formulate the Multiple Kernel Learning (abbreviated as MKL) problem for the support vector machine with the infamous (0,1)-loss function. Some first-order optimality conditions are given and then exploited to develop a fast ADMM solver for the nonconvex and nonsmooth optimization problem. A simple numerical experiment on synthetic planar data shows that our MKL-L_0/1-SVM framework could be promising.