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On Rationality of Nonnegative Matrix Factorization [PDF]

Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, 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. NMF has a wide variety of applications, including bioinformatics, chemometrics, communication complexity, machine learning, polyhedral combinatorics, among many others ...
Chistikov, Dmitry, Kiefer, Stefan, Marušic, Ines, Shirmohammadi, Mahsa, Worrell, James   +4 more
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Descent Methods for Nonnegative Matrix Factorization [PDF]

, 2011
47 pages. New convergence proof using damped version of RRI. To appear in Numerical Linear Algebra in Signals, Systems and Control. Accepted.
Ho, Ngoc-Diep, Van Dooren, Paul, Blondel, Vincent D.   +2 more
openaire   +2 more sources

Multi-constraint non-negative matrix factorization for community detection: orthogonal regular sparse constraint non-negative matrix factorization

Complex & Intelligent Systems
Community detection is an important method to analyze the characteristics and structure of community networks, which can excavate the potential links between nodes and further discover subgroups from complex networks.
Zigang Chen, Qi Xiao, Tao Leng, Zhenjiang Zhang, Ding Pan, Yuhong Liu, Xiaoyong Li   +6 more
doaj   +1 more source

Discriminative Multiview Nonnegative Matrix Factorization for Classification

IEEE Access, 2019
Multiview nonnegative matrix has shown many promising applications in computer vision and pattern recognition. However, most existing works focus on view consistency and ignore discrimination.
Weihua Ou, Jianping Gou, Quan Zhou, Shiming Ge, Fei Long   +4 more
doaj   +1 more source

Multimode Process Monitoring Method Based on Multiblock Projection Nonnegative Matrix Factorization

Advances in Mathematical Physics, 2020
A multimode process monitoring method based on multiblock projection nonnegative matrix factorization (MPNMF) is proposed for traditional process monitoring methods which often adopt global model of data and ignore local information of data. Firstly, the
Yan Wang, Yu-Bo Zhao, Chuang Li, Chuan-Qian Zhu, Shuai-shuai Han, Xiao-Guang Gu   +5 more
doaj   +1 more source

Graph Regularized Constrained Non-Negative Matrix Factorization With Lₚ Smoothness for Image Representation

IEEE Access, 2020
Nonnegative matrix factorization-based image representation algorithms have been widely applied to deal with high-dimensional data in the past few years.
Zhenqiu Shu, Zonghui Weng, Yunmeng Zhang, Cong-Zhe You, Zhen Liu   +4 more
doaj   +1 more source

On Restricted Nonnegative Matrix Factorization

, 2016
Full version of an ICALP'16 ...
Chistikov, D, Kiefer, S, Marusic, I, Shirmohammadi, M, Worrell, J   +4 more
openaire   +5 more sources

Similarity Learning-Induced Symmetric Nonnegative Matrix Factorization for Image Clustering

IEEE Access, 2019
As a typical variation of nonnegative matrix factorization (NMF), symmetric NMF (SNMF) is capable of exploiting information of the cluster embedded in the matrix of similarity.
Wei Yan, Bob Zhang, Zuyuan Yang, Shengli Xie   +3 more
doaj   +1 more source

Sparsity induced convex nonnegative matrix factorization algorithm with manifold regularization

Tongxin xuebao, 2020
To address problems that the effectiveness of feature learned from real noisy data by classical nonnegative matrix factorization method,a novel sparsity induced manifold regularized convex nonnegative matrix factorization algorithm (SGCNMF) was proposed ...
Feiyue QIU, Bowen CHEN, Tieming CHEN, Guodao ZHANG   +3 more
doaj   +2 more sources

Parallel Nonnegative Matrix Factorization with Manifold Regularization

Journal of Electrical and Computer Engineering, 2018
Nonnegative matrix factorization (NMF) decomposes a high-dimensional nonnegative matrix into the product of two reduced dimensional nonnegative matrices.
Fudong Liu, Zheng Shan, Yihang Chen
doaj   +1 more source