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Face Recognition via Locality Constrained Low Rank Representation and
Dictionary Learning, Version 1.0 Copyright(c) 2017 He-Feng Yin, Xiao-Jun Wu
All Rights Reserved.

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Permission to use, copy, or modify this software and its documentation
for educational and research purposes only and without fee is here
granted, provided that this copyright notice and the original authors'
names appear on all copies and supporting documentation. This program
shall not be used, rewritten, or adapted as the basis of a commercial
software or hardware product without first obtaining permission of the
authors. The authors make no representations about the suitability of
this software for any purpose. It is provided "as is" without express
or implied warranty.
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Please refer to the following paper

He-Feng Yin and Xiao-Jun Wu "Face Recognition via Locality Constrained
Low Rank Representation and Dictionary Learning," https://arxiv.org/abs/1912.03145
Contact: [email protected]
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Toolbox of lrr can be downloaded from https://sites.google.com/site/guangcanliu/lrr.zip?attredirects=0&d=1
demo_YaleB.m provides a demo for face recognition in Extended Yale B database
(Sample rate is 1/2 and the number of training samples for each subject is 32)

WLRR.m is a function implementing our proposed Locality Constrained Low Rank
Representation and Dictionary Learning (LCLRRDL).

L2_distance.m is a function that constructs the weight matrix.