Results 11 to 20 of about 14,760 (255)

Co-sparse Non-negative Matrix Factorization [PDF]

open access: yesFrontiers in Neuroscience, 2022
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]

open access: yesPLoS ONE, 2013
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

open access: yesBioData Mining, 2017
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

open access: yesnpj Computational Materials
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]

open access: yesNature Communications
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]

open access: yesBMC Bioinformatics, 2023
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]

open access: yesPeerJ
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]

open access: yesGenome Biology
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]

open access: yesEntropy
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]

open access: yesGenome Biology
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

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