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Graph Regularized Nonnegative Matrix Factorization with Sparse Coding
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-15
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
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 intrinsic manifold structure and also the local features of original data.
The target function of our method is easy to propose, while the solving procedures are really nontrivial; in the paper we gave the detailed derivation of solving the target function and also a strict proof of its convergence, which is a key contribution of the paper.
Compared with sparseness constrained NMF and GNMF algorithms, GRNMF_SC can learn much sparser representation of the data and can also preserve the geometrical structure of the data, which endow it with powerful discriminating ability.
Furthermore, the GRNMF_SC is generalized as supervised and unsupervised models to meet different demands.
Experimental results demonstrate encouraging results of GRNMF_SC on image recognition and clustering when comparing with the other state-of-the-art NMF methods.
American Psychological Association (APA)
Lin, Chuang& Pang, Meng. 2015. Graph Regularized Nonnegative Matrix Factorization with Sparse Coding. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073295
Modern Language Association (MLA)
Lin, Chuang& Pang, Meng. Graph Regularized Nonnegative Matrix Factorization with Sparse Coding. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1073295
American Medical Association (AMA)
Lin, Chuang& Pang, Meng. Graph Regularized Nonnegative Matrix Factorization with Sparse Coding. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073295
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073295