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Graph Regularized Nonnegative Matrix Factorization with Sparse Coding

In this paper, we propose a sparseness constraint NMF method, named graph regularized matrix factorization with sparse coding (GRNMF_SC). By combining manifold learning and sparse coding techniques together, GRNMF_SC can efficiently extract the basic vectors from the data space, which preserves the...

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Main Authors: Chuang Lin, Meng Pang
格式: Artigo
語言:Inglês
出版: Hindawi Limited 2015-01-01
叢編:Mathematical Problems in Engineering
在線閱讀:http://dx.doi.org/10.1155/2015/239589
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