Low-rank preserving embedding.

Pattern Recognition（2017）

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摘要

•Using low-rank representation for dimension reduction (LRPE).•LRPE retains global discriminative structure into reduced space.•Recast related methods into a unified problem and then tackle it.•LRPE is more effective and robust, as well as cheap computation.

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关键词

Low-rank representation,Dimensionality reduction,Discriminative feature learning,Reconstruction relationship preserving projections

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