A Convex Sparse PCA for Feature Analysis

23 Nov 2014 Xiaojun Chang Feiping Nie Yi Yang Heng Huang

Principal component analysis (PCA) has been widely applied to dimensionality reduction and data pre-processing for different applications in engineering, biology and social science. Classical PCA and its variants seek for linear projections of the original variables to obtain a low dimensional feature representation with maximal variance... (read more)

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Dimensionality Reduction