Results 321 to 330 of about 2,535,217 (348)

Positive and Negative Label-Driven Nonnegative Matrix Factorization

IEEE transactions on circuits and systems for video technology (Print), 2020
Positive label is often used as the supervisory information in the learning scenario, which refers to the category that a sample is assigned to. However, another side information lying in the labels, which describes the categories that a sample is ...
Wenhui Wu, Yuheng Jia, Shiqi Wang, Ran Wang, Hongfei Fan, S. Kwong   +5 more
semanticscholar   +1 more source

Parallelism on the Nonnegative Matrix Factorization

2012
A great interest has been given to the Nonnegative Matrix Factorization (NMF) due to its ability of extracting highly-interpretable parts from data sets. Nonetheless, its usage is hindered by the computational complexity when processing large matrices.
Edgardo Mejía-Roa, Carlos García 0001, José Ignacio Gómez, Manuel Prieto 0001, Christian Tenllado, Alberto D. Pascual-Montano, Francisco Tirado   +6 more
openaire   +1 more source

Nonnegative Rank Factorization of a Nonnegative Matrix A with A A ≥0

Linear and Multilinear Algebra, 2003
In this article we obtain a nonnegative rank factorization of nonnegative matrices A satisfying one or both of the following conditions: (i) AA † ⩽ 0 (ii) A † A ⩽ 0, thus providing a new set of conditions that guarantee the existence of a nonnegative least-squares solution of a linear system.
S.K. Jain, John Tynan
openaire   +1 more source

On Nonnegative Solutions of Matrix Equations

SIAM Journal on Algebraic Discrete Methods, 1985
Let A be a nontrivial nonnegative matrix, b a nontrivial nonnegative vector, and \(\lambda\) a positive number. Using the Frobenius structure of A, the author gives necessary and sufficient conditions for the existence of a nonnegative vector x such that \((\lambda I-A)x=b\).
openaire   +1 more source

Robust graph regularization nonnegative matrix factorization for link prediction in attributed networks

Multimedia tools and applications, 2022
E. Nasiri, K. Berahmand, Yuefeng Li
semanticscholar   +1 more source

Deep asymmetric nonnegative matrix factorization for graph clustering

Pattern Recognition, 2023
Akram Hajiveiseh, Seyed Amjad Seyedi, F. Tab   +2 more
semanticscholar   +1 more source

The Nonnegative Matrix Factorization: Regularization and Complexity

SIAM Journal on Scientific Computing, 2016
Summary: Data continues to grow, and it has become ever important to find effective big data analysis techniques. Computational tools, such as singular value decomposition, have been employed in the interpretation of big data. Another tool has recently gained popularity and comparative success: the nonnegative matrix factorization (NMF). The NMF method
Kazufumi Ito, A. K. Landi
openaire   +1 more source

On the Elasticity of the Perron Root of a Nonnegative Matrix

SIAM Journal on Matrix Analysis and Applications, 2002
The paper deals with the elasticity of the Perron root \(\lambda\) with respect to \(a_{ij}\), \[ e_{ij}= \frac{a_{ij}}{\lambda} \frac{\partial \lambda}{\partial a_{ij}}, \quad i,j = 1,2,\dots, n, \] where \(A=(a_{ij})\) is an \(n \times n\) nonnegative irreducible matrix.
Stephen J. Kirkland, Michael Neumann, N. Ormes, Jianhong Xu   +3 more
openaire   +1 more source

Adaptive graph nonnegative matrix factorization with the self-paced regularization

Applied intelligence (Boston), 2022
Xuanhao Yang, Hangjun Che, Man-Fai Leung, Cheng Liu   +3 more
semanticscholar   +1 more source

A survey of deep nonnegative matrix factorization

Neurocomputing, 2022
Wensheng Chen, Qianwen Zeng, Binbin Pan
semanticscholar   +1 more source