Year: 2012
Journal of Computational Mathematics, Vol. 30 (2012), Iss. 1 : pp. 34–46
Abstract
The orthogonal nonnegative matrix factorization (ONMF) has many applications in a variety of areas such as data mining, information processing and pattern recognition. In this paper, we propose a novel initialization method for the ONMF based on the Lanczos bidiagonalization and the nonnegative approximation of rank one matrix. Numerical experiments are given to show that our initialization strategy is effective and efficient.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/jcm.1110-m11si10
Journal of Computational Mathematics, Vol. 30 (2012), Iss. 1 : pp. 34–46
Published online: 2012-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 13
Keywords: Lanczos bidiagonalization Orthogonal nonnegative matrix factorization Low-rank approximation Nonnegative approximation.