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Communication Dans Un Congrès Année : 2008

A Fast Method for Training Linear SVM in the Primal

Résumé

We propose a new algorithm for training a linear Support Vector Machine in the primal. The algorithm mixes ideas from non smooth optimization, subgradient methods, and cutting planes methods. This yields a fast algorithm that compares well to state of the art algorithms. It is proved to require O(1/λε) iterations to converge to a solution with accuracy ε. Additionally we provide an exact shrinking method in the primal that allows reducing the complexity of an iteration to much less than O(N) where N is the number of training samples.

Dates et versions

hal-01301600 , version 1 (12-04-2016)

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Trinh Minh Tri Do, Thierry Artières. A Fast Method for Training Linear SVM in the Primal. European Conference on Machine Learning (ECML), Sep 2008, Antwerp, Belgium. pp.272-287, ⟨10.1007/978-3-540-87479-9_36⟩. ⟨hal-01301600⟩
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