Results 31 to 40 of about 1,727,048 (195)
Entropy, 2017 Semi-Nonnegative Matrix Factorization (Semi-NMF), as a variant of NMF, inherits the merit of parts-based representation of NMF and possesses the ability to process mixed sign data, which has attracted extensive attention. However, standard Semi-NMF still
Peng Luo, Jinye Peng
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, 2022 Multiple graph and semi-supervision techniques have been successfully introduced into the nonnegative matrix factorization (NMF) model for taking full advantage of the manifold structure and priori information of data to capture excellent low-dimensional
Yi Wang +11 more
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Robust Graph Regularized Nonnegative Matrix Factorization
IEEE Access, 2022 Nonnegative Matrix Factorization (NMF) has become a popular technique for dimensionality reduction, and been widely used in machine learning, computer vision, and data mining. Existing unsupervised NMF methods impose the intrinsic geometric constraint on
Qi Huang +3 more
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Spectro-temporal post-enhancement using MMSE estimation in NMF based single-channel source separation [PDF]
, 2013 We propose to use minimum mean squared error (MMSE) estimates to enhance the signals that are separated by nonnegative matrix factorization (NMF). In single channel source separation (SCSS), NMF is used to train a set of basis vectors for each source ...
Erdoğan, Hakan, Grais, Emad Mounir
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IEEE Access, 2020 Community detection is a critical issue in the field of complex networks. Recently, the nonnegative matrix factorization (NMF) method has successfully uncovered the community structure in the complex networks.
Hong Lu +3 more
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Directional clustering through matrix factorization [PDF]
, 2016 This paper deals with a clustering problem where feature vectors are clustered depending on the angle between feature vectors, that is, feature vectors are grouped together if they point roughly in the same direction.
Blumensath, Thomas
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Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Hyperspectral unmixing has been an important technique that estimates a set of endmembers and their corresponding abundances from a hyperspectral image (HSI).
Xin-Ru Feng +5 more
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A projective approach to nonnegative matrix factorization [PDF]
, 2021 In data science and machine learning, the method of nonnegative matrix factorization (NMF) is a powerful tool that enjoys great popularity. Depending on the concrete application, there exist several subclasses each of which performs a NMF under certain ...
Groetzner, Patrick
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Nonnegative matrix factorization requires irrationality [PDF]
, 2017 Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n × m matrix M into a product of a nonnegative n × d matrix W and a nonnegative d × m matrix H. A longstanding open question, posed by Cohen and Rothblum in 1993, is
Kiefer, Stefan +9 more
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Hybridizing sparse component analysis with genetic algorithms for microarray analysis [PDF]
, 2008 Nonnegative matrix factorization (NMF) has proven to be a useful tool for the analysis of nonnegative multivariate data. However, it is known not to lead to unique results when applied to blind source separation (BSS) problems.
Stadlthanner, K. +9 more
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