Fast Nonnegative Matrix Factorization: An Active-Set-Like Method and Comparisons
نویسندگان
چکیده
منابع مشابه
Fast Nonnegative Matrix Factorization: An Active-Set-Like Method and Comparisons
Nonnegative matrix factorization (NMF) is a dimension reduction method that has been widely used for numerous applications including text mining, computer vision, pattern discovery, and bioinformatics. A mathematical formulation for NMF appears as a non-convex optimization problem, and various types of algorithms have been devised to solve the problem. The alternating nonnegative least squares ...
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The non-negative matrix factorization (NMF) determines a lower rank approximation of a matrix where an interger "!$# is given and nonnegativity is imposed on all components of the factors % & (' and % )'* ( . The NMF has attracted much attention for over a decade and has been successfully applied to numerous data analysis problems. In applications where the components of the data are necessaril...
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Nonnegative factorization of tensors plays an important role in the analysis of multi-dimensional data in which each element is inherently nonnegative. It provides a meaningful lower rank approximation, which can further be used for dimensionality reduction, data compression, text mining, or visualization. In this paper, we propose a fast algorithm for nonnegative tensor factorization (NTF) bas...
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ژورنال
عنوان ژورنال: SIAM Journal on Scientific Computing
سال: 2011
ISSN: 1064-8275,1095-7197
DOI: 10.1137/110821172