F-SVM: Combination of Feature Transformation and SVM Learning via Convex Relaxation

20 Apr 2015Xiaohe WuWangmeng ZuoYuanyuan ZhuLiang Lin

The generalization error bound of support vector machine (SVM) depends on the ratio of radius and margin, while standard SVM only considers the maximization of the margin but ignores the minimization of the radius. Several approaches have been proposed to integrate radius and margin for joint learning of feature transformation and SVM classifier... (read more)

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