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Exact SVM training by Wolfe's minimum norm point algorithm | IEEE Conference Publication | IEEE Xplore

Exact SVM training by Wolfe's minimum norm point algorithm


Abstract:

This paper applies Wolfe's algorithm for finding the minimum norm point in a polytope to training of standard SVM with hinge loss. The resulting algorithm is guaranteed t...Show More

Abstract:

This paper applies Wolfe's algorithm for finding the minimum norm point in a polytope to training of standard SVM with hinge loss. The resulting algorithm is guaranteed to obtain an exact optimal solution within a finite number of iterations. Experiments illustrate that our algorithm runs faster than existing algorithms such as LIBSVM for the same model. In comparison with LIBLINEAR, which adopts a variant of SVMs, our approach works better when the feature size is modest; the feature size is sufficiently smaller than the sample size.
Date of Conference: 21-24 September 2014
Date Added to IEEE Xplore: 20 November 2014
Electronic ISBN:978-1-4799-3694-6

ISSN Information:

Conference Location: Reims, France

References

References is not available for this document.