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Discriminant analysis (DA) is a well-known dimensionality reduction tool in pattern classification. With enough efficient labeled samples, the optimal projections could be found by maximizing the between-class scatter variance meanwhile minimizing the within-class scatter variance. However, the acquisition of label information is difficult in practice. So, semi-supervised discriminant analysis has...
In this paper a generalized tensor subspace model is concluded from the existing tensor dimensionality reduction algorithms. With this model, we investigate the orthogonality of the bases of the high-order tensor subspace, and propose the Orthogonal Tensor Neighborhood Preserving Embedding (OTNPE) algorithm. We evaluate the algorithm by applying it to facial expression recognition, where both the...
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