Title:
Approximate low-rank projection1
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Description: 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
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File list (Check if you may need any files):
| Filename | Size | Date |
|---|
| Approximate low-rank projection\Approximate Low-Rank Projection Learning for Feature Extraction.pdf | 2755969 | 2019-12-26
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| Approximate low-rank projection\Supervised\Pre_label.m | 332 | 2015-08-24
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| Approximate low-rank projection\Supervised\Recognition_LatLRR.m | 1852 | 2016-03-02
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| Approximate low-rank projection\Unsupervised\Improve_LRR.m | 1724 | 2015-06-21
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| Approximate low-rank projection\Supervised | 0 | 2020-01-21
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| Approximate low-rank projection\Unsupervised | 0 | 2020-01-21
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| Approximate low-rank projection | 0 | 2020-02-01 |
