In recent years, symmetric non-negative matrix factorization (SNMF), a variant of non-
negative matrix factorization (NMF), has emerged as a promising tool for data analysis. This …

Although nonnegative matrix factorization (NMF) is widely used, some matrix factorization
methods result in misleading results and waste of computing resources due to lack of timely …

Community detection is a popular yet thorny issue in social network analysis. A symmetric
and nonnegative matrix factorization (SNMF) model based on a nonnegative multiplicative …

Most recent graph clustering methods have resorted to Graph Auto-Encoders (GAEs) to
perform joint clustering and embedding learning. However, two critical issues have been …

In this article, we propose a semi-supervised non-negative matrix factorization (NMF) model
by means of elegantly modeling the label information. The proposed model is capable of …

As a variant of non-negative matrix factorization (NMF), symmetric NMF (SymNMF) can
generate the clustering result without additional post-processing, by decomposing a …

Community describes the functional mechanism of an undirected network, making
community detection a fundamental tool for graph representation learning-related …

Semi-supervised nonnegative matrix factorization (NMF) has received considerable
attention in machine learning and data mining. A new semi-supervised NMF method, called …

Nonnegative matrix factorization (NMF) based multiview technique has been commonly
used in multiview data clustering tasks. However, previous NMF based multiview clustering …

Graph-regularized non-negative matrix factorization (GNMF) is proved to be effective for the
clustering of nonlinear separable data. Existing GNMF variants commonly improve model …