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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...

पूर्ण विवरण

में बचाया:
ग्रंथसूची विवरण
मुख्य लेखकों: Chuang Lin, Meng Pang
स्वरूप: Artigo
भाषा:Inglês
प्रकाशित: Hindawi Limited 2015-01-01
श्रृंखला:Mathematical Problems in Engineering
ऑनलाइन पहुंच:http://dx.doi.org/10.1155/2015/239589
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