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Support vector machine (SVM) is a supervised method widely used in the statistical classification and regression analysis. SVM training can be solved via the interior point method (IPM) with the advantages of low storage, fast convergence and easy parallelization. However, it is still confronted with the challenges of training speed and memory use. In this paper, we propose a parallel primal-dual...
Support vector machine (SVM) is a supervised method widely used in the statistical classification and regression analysis. SVM training can be solved via the interior point method (IPM) with the advantages of low storage, fast convergence and easy parallelization. However, it is still confronted with the challenges of training speed and memory use. In this paper, we propose a parallel primal-dual...
Clustering is one of the most fundamental and important problems in computer vision and pattern recognition communities. Maximum margin clustering (MMC) is a recently proposed clustering technique which has shown promising experimental results. The main theme behind MMC is to extend the standard maximum margin principle in support vector machine (SVM) to the unsupervised scenario. This paper will...
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