Zeng-Shun Zhao

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—In this paper, we show how to learn a good similarity metric for SVM classification. We present a novel approach to simultaneously learn a Mahalanobis similarity metric and an SVM classifier. Different from previous approaches, we optimize the Mahalanobis metric directly for minimizing the SVM classification error. Our formulation generalizes the(More)