Results 101 to 110 of about 2,052,954 (190)

Nonnegative Matrix Factorization Problem

, 2020
The Nonnegative Matrix Factorization (NMF) problem has been widely used to analyze high-dimensional nonnegative data and extract important features. In this paper, I review major concepts regarding NMF, some NMF algorithms and related problems including ...
An, Junda
core  

Surrogate Computational Homogenization Enhanced by Partition‐of‐Unity RBF Interpolation With Decision Trees

International Journal for Numerical Methods in Engineering, Volume 127, Issue 20, 30 October 2026.
ABSTRACT This study enhances a framework of surrogate computational homogenization (SCH) using decision tree‐based partition‐of‐unity radial basis function (PU‐RBF) interpolation for three‐dimensional finite‐deformation two‐scale analysis. The method addresses the scalability limitation of global RBF interpolation for large numerical material test (NMT)
Yosuke Yamanaka, Norio Hirayama, Kenjiro Terada   +2 more
wiley   +1 more source

NONNEGATIVE MATRIX FACTORIZATION

, 2013
The purpose of this project was to study the nonnegative matrix factorization (NNMF) problem: Given a nonnegative matrix V, find the” best” nonnegative matrices W and H, such that V WH.
Humpherys, Dr. Jeffrey, Schillemat, Gretchen   +1 more
core  

Rethinking Symmetric Matrix Factorization: A More General and Better Clustering Perspective

, 2023
Nonnegative matrix factorization (NMF) is widely used for clustering with strong interpretability. Among general NMF problems, symmetric NMF is a special one that plays an important role in graph clustering where each element measures the similarity ...
Zhang, Mengyuan, Liu, Kai
core  

Community detection via graph regularized symmetric nonnegative matrix tri-factorization

The Journal of Supercomputing
Abstract Identifying meaningful communities in complex networks is essential for uncovering functional structures in social, biological, and technological systems. Despite the success of Nonnegative Matrix Factorization (NMF) methods, most existing approaches fail to simultaneously preserve local structural ...
Hazhir Sohrabi, Shahrokh Esmaeili, Parham Moradi   +2 more
openaire   +2 more sources

Robust Structure Preserving Nonnegative Matrix Factorization for Dimensionality Reduction

, 2016
As a linear dimensionality reduction method, nonnegative matrix factorization (NMF) has been widely used in many fields, such as machine learning and data mining.
Li BF(李冰锋), Han Z(韩志), Tang YD(唐延东)   +2 more
core  

Community-Based Matrix Factorization (CBMF) Approach for Enhancing Quality of Recommendations. [PDF]

Entropy (Basel), 2023
Tokala S, Enduri MK, Lakshmi TJ, Sharma H.   +3 more
europepmc   +1 more source

A Novel Initialization Method for Symmetric Nonnegative Matrix Factorization [PDF]

Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016), 2017
Haoxia Huang, Jianqiang Wu
openaire   +1 more source

L1/2 Sparsity Constrained Nonnegative Matrix Factorization for Hyperspectral Unmixing

, 2010
L1/2 Sparsity Constrained Nonnegative Matrix Factorization for Hyperspectral ...
Yuntao Qian (782935), Sen Jia (2163685), Antonio Robles-Kelly (13058748), Jun Zhou (6477)   +3 more
core  

Efficient hybrid algorithm for nonnegative matrix factorization based on modified nonmonotone linear search. [PDF]

PLoS One
Wu J, Li W, Su L, Wang H, Li Y.
europepmc   +1 more source