Feature extraction plays a significant role in pattern recognition. Recently, many representation-based feature extraction methods have been proposed and achieved successes in many applications. As an excellent unsupervised feature extraction method, latent low-rank representation (LatLRR) has shown its power in extracting salient features

Filename	Size	Update
Approximate low-rank projection\Approximate Low-Rank Projection Learning for Feature Extraction.pdf	2755969	2019-12-26
Approximate low-rank projection\Supervised\Pre_label.m	332	2015-08-24
Approximate low-rank projection\Supervised\Recognition_LatLRR.m	1852	2016-03-02
Approximate low-rank projection\Unsupervised\Improve_LRR.m	1724	2015-06-21
Approximate low-rank projection\Supervised	0	2020-01-21
Approximate low-rank projection\Unsupervised	0	2020-01-21
Approximate low-rank projection	0	2020-02-01

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