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Learning Sign-Constrained Support Vector Machines
One of the two algorithms is based on the projected gradient method, in which each iteration of the projected gradient method takes $O(nd)$ computational cost and the sublinear convergence of the objective error is guaranteed.
Frank-Wolfe algorithm for learning SVM-type multi-category classifiers
In this study, we developed a new optimization algorithm that can be applied to many of MC-SVM variants.
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