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arXiv · 1210.0699

TV-SVM: Total Variation Support Vector Machine for Semi-Supervised Data Classification

Xavier Bresson·Ruiliang Zhang
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Abstract

We introduce semi-supervised data classification algorithms based on total variation (TV), Reproducing Kernel Hilbert Space (RKHS), support vector machine (SVM), Cheeger cut, labeled and unlabeled data points. We design binary and multi-class semi-supervised classification algorithms. We compare the TV-based classification algorithms with the related Laplacian-based algorithms, and show that TV classification perform significantly better when the number of labeled data is small.

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Xavier Bresson, Ruiliang Zhang. 2012-10-02. TV-SVM: Total Variation Support Vector Machine for Semi-Supervised Data Classification. https://arxiv.org/abs/1210.0699

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