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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
openaire   +2 more sources

A Fast Gradient Method for Nonnegative Sparse Regression with Self Dictionary

, 2017
A nonnegative matrix factorization (NMF) can be computed efficiently under the separability assumption, which asserts that all the columns of the given input data matrix belong to the cone generated by a (small) subset of them.
Gillis, Nicolas, Luce, Robert
core   +1 more source

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

A multilevel approach for nonnegative matrix factorization [PDF]

Nonnegative Matrix Factorization (NMF) is the problem of approximating a nonnegative matrix with the product of two low-rank nonnegative matrices and has been shown to be particularly useful in many applications, e.g., in text mining, image processing ...
GILLIS, Nicolas, GLINEUR, François
core  

Accelerating Nonnegative Matrix Factorization Algorithms using Extrapolation

, 2018
In this paper, we propose a general framework to accelerate significantly the algorithms for nonnegative matrix factorization (NMF). This framework is inspired from the extrapolation scheme used to accelerate gradient methods in convex optimization and ...
Ang, Andersen Man Shun, Gillis, Nicolas
core   +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

Ranking Preserving Nonnegative Matrix Factorization [PDF]

, 2018
Nonnegative matrix factorization (NMF), a wellknown technique to find parts-based representations of nonnegative data, has been widely studied. In reality, ordinal relations often exist among data, such as data i is more related to j than to q. Such
Liu, W., Tian, Feng, Wang, Jing, Wang, X.   +3 more
core  

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