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Standard unsupervised linear feature extraction methods find orthonormal (PCA) or statistically independent (ICA) latent variables that are good for data representation. These representative features may not be optimal for the classification tasks, thus requiring a search of linear projections that can give a good discriminative model. A semi-supervised linear feature extraction method, namely dICA,...
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