Novel Algorithms Based on Majorization Minimization for Nonnegative Matrix Factorization
نویسندگان
چکیده
منابع مشابه
Approximate Nonnegative Matrix Factorization via Alternating Minimization
In this paper we consider the Nonnegative Matrix Factorization (NMF) problem: given an (elementwise) nonnegative matrix V ∈ R + find, for assigned k, nonnegative matrices W ∈ R + and H ∈ R k×n + such that V = WH . Exact, non trivial, nonnegative factorizations do not always exist, hence it is interesting to pose the approximate NMF problem. The criterion which is commonly employed is I-divergen...
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The nonnegative matrix factorization (NMF) is a boundconstrained low-rank approximation technique for nonnegative multivariate data. NMF has been studied extensively over the last years, but an important aspect which only has received little attention so far is a proper initialization of the NMF factors in order to achieve a faster error reduction. Since the NMF objective function is usually no...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2019
ISSN: 2169-3536
DOI: 10.1109/access.2019.2933845