Co-sparse Non-negative Matrix Factorization [PDF]
Non-negative matrix factorization, which decomposes the input non-negative matrix into product of two non-negative matrices, has been widely used in the neuroimaging field due to its flexible interpretability with non-negativity property.
Fan Wu +3 more
doaj +5 more sources
Discriminant projective non-negative matrix factorization. [PDF]
Projective non-negative matrix factorization (PNMF) projects high-dimensional non-negative examples X onto a lower-dimensional subspace spanned by a non-negative basis W and considers W(T) X as their coefficients, i.e., X≈WW(T) X.
Naiyang Guan +4 more
doaj +4 more sources
Scalable non-negative matrix tri-factorization
Background Matrix factorization is a well established pattern discovery tool that has seen numerous applications in biomedical data analytics, such as gene expression co-clustering, patient stratification, and gene-disease association mining.
Andrej Čopar +2 more
doaj +3 more sources
Stretched non-negative matrix factorization
A novel algorithm, stretchedNMF, is introduced for non-negative matrix factorization (NMF), accounting for signal stretching along the independent variable’s axis.
Ran Gu +11 more
doaj +3 more sources
In-memory analog computing for non-negative matrix factorization [PDF]
Non-negative matrix factorization (NMF) is a powerful technique for extracting latent structures from high-dimensional data, with applications spanning recommender systems, bioinformatics, and image processing.
Shiqing Wang +6 more
doaj +2 more sources
Graph regularized non-negative matrix factorization with $$L_{2,1}$$ L 2 , 1 norm regularization terms for drug–target interactions prediction [PDF]
Background Identifying drug–target interactions (DTIs) plays a key role in drug development. Traditional wet experiments to identify DTIs are costly and time consuming. Effective computational methods to predict DTIs are useful to speed up the process of
Junjun Zhang, Minzhu Xie
doaj +2 more sources
JGR-NMF: joint graph-regularized non-negative matrix factorization for spatial domain identification [PDF]
The spatial transcriptomics technique provides an unprecedented perspective for analyzing the distribution patterns of cells within tissues and their functional tissue structures.
Juan Liang +4 more
doaj +3 more sources
Bayesian multi-study non-negative matrix factorization for mutational signatures [PDF]
Mutational signatures are typically identified from tumor genome sequencing data using non-negative matrix factorization (NMF). However, existing NMF techniques only decompose a single dataset, limiting rigorous comparisons of signatures across ...
Isabella N. Grabski +2 more
doaj +2 more sources
Autoencoder-like Sparse Non-Negative Matrix Factorization with Structure Relationship Preservation [PDF]
Clustering algorithms based on non-negative matrix factorization (NMF) have garnered significant attention in data mining due to their strong interpretability and computational simplicity.
Ling Zhong, Haiyan Gao
doaj +2 more sources
Non-negative matrix factorization and deconvolution as a dual simplex problem [PDF]
Background Non-negative matrix factorization is a powerful linear algebra tool used in multiple areas of data analysis, including computational biology.
Denis Kleverov +3 more
doaj +2 more sources

