Tight Semi-nonnegative Matrix Factorization
نویسندگان
چکیده
منابع مشابه
Tight Semi-Nonnegative Matrix Factorization
The nonnegative matrix factorization is a widely used, flexible matrix decomposition, finding applications in biology, image and signal processing and information retrieval, among other areas. Here we present a related matrix factorization. A multi-objective optimization problem finds conical combinations of templates that approximate a given data matrix. The templates are chosen so that as far...
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Given a matrix M (not necessarily nonnegative) and a factorization rank r, semi-nonnegative matrix factorization (semi-NMF) looks for a matrix U with r columns and a nonnegative matrix V with r rows such that UV is the best possible approximation of M according to some metric. In this paper, we study the properties of semi-NMF from which we develop exact and heuristic algorithms. Our contributi...
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ژورنال
عنوان ژورنال: Pattern Recognition and Image Analysis
سال: 2020
ISSN: 1054-6618,1555-6212
DOI: 10.1134/s1054661820040124