Matrix exponential based semi-supervised discriminant embedding for image classification

@article{Dornaika2017MatrixEB,
  title={Matrix exponential based semi-supervised discriminant embedding for image classification},
  author={Fadi Dornaika and Youssof El Traboulsi},
  journal={Pattern Recognition},
  year={2017},
  volume={61},
  pages={92-103}
}
Semi-supervised Discriminant Embedding (SDE) is the semi-supervised extension of Local Discriminant Embedding (LDE). Since this type of methods is in general dealing with high dimensional data, the smallsample-size (SSS) problem very often occurs. This problem occurs when the number of available samples is less than the sample dimension. The classic solution to this problem is to reduce the dimension of the original data so that the reduced number of features is less than the number of samples… CONTINUE READING
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