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In this brief, we give a new proof of the asymptotic convergence of the sequential minimum optimization (SMO) algorithm for both the most violating pair and second order rules to select the pair of coefficients to be updated. The proof is more self-contained, shorter, and simpler than previous ones and has a different flavor, partially building upon Gilbert's original convergence proof of its algorithm...
Scaled Convex Hulls (SCHs) have been recently proposed by Liu et al. as the basis of a method to build linear classifiers that, when extended to kernel settings, provides an alternative approach to more established methods such as SVMs. Here we show how to adapt the Mitchell-Dem'yanov-Malozemov (MDM) algorithm to build such SCH-based classifiers by solving a concrete nearest point problem. We shall...
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