Multiview Privileged Support Vector Machines

  title={Multiview Privileged Support Vector Machines},
  author={Jingjing Tang and Yingjie Tian and Peng Zhang and Xiaohui Liu},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
Multiview learning (MVL), by exploiting the complementary information among multiple feature sets, can improve the performance of many existing learning tasks. Support vector machine (SVM)-based models have been frequently used for MVL. A typical SVM-based MVL model is SVM-2K, which extends SVM for MVL by using the distance minimization version of kernel canonical correlation analysis. However, SVM-2K cannot fully unleash the power of the complementary information among different feature views… CONTINUE READING
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