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The method of Lagrange multipliers finds critical points (including maxima and minima) of a differentiable function subject to differentiable constraints.
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Why are the Lagrange multipliers sparse for SVMs?
I've read that for the Maximal Margin Classifier SVM, after solving the dual problem, most of the lagrange multipliers turn out to be zeros. Only the ones corresponding to the support vectors turn out …