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《Computer Engineering and Applications》 2011-20
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Semi-supervised dimensionality reduction based on sparsity representation

ZHANG Chuntao,GUO Jiao,Xu Jialiang College of Mathematics and Computer Science,Chongqing Three Gorges University,Chongqing 404100,China  
A Semi-Supervised Dimensionality Reduction method based on Sparsity Representation(SpSSDR) is proposed.Unlike other semi-supervised dimensionality reduction methods that construct graphs in steps,SpSSDR simultaneously defines the connectivity and the edges’weights of a graph via sparsity reconstruction coefficients,and then exploits pairwise constraints for dimensionality reduction.Experiments on high dimensional facial data show that SpSSDR is not only robust to noise but also making use of pairwise constraints efficiently.
【Fund】: 重庆市教委科技项目(No.KJ111106)
【CateGory Index】: TP391.41
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