Results 1 to 10 of about 112,822 (316)

Discriminant projective non-negative matrix factorization. [PDF]

PLoS 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, Xiang Zhang, Zhigang Luo, Dacheng Tao, Xuejun Yang   +4 more
doaj   +11 more sources

Co-sparse Non-negative Matrix Factorization [PDF]

Frontiers 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, Jiahui Cai, Canhong Wen, Haizhu Tan   +3 more
doaj   +5 more sources

Scalable non-negative matrix tri-factorization

BioData 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, Marinka žitnik, Blaž Zupan   +2 more
doaj   +5 more sources

Optimization and expansion of non-negative matrix factorization [PDF]

BMC Bioinformatics, 2020
Background Non-negative matrix factorization (NMF) is a technique widely used in various fields, including artificial intelligence (AI), signal processing and bioinformatics.
Xihui Lin, Paul C. Boutros
doaj   +5 more sources

Stretched non-negative matrix factorization

npj 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, Yevgeny Rakita, Ling Lan, Zach Thatcher, Gabrielle E. Kamm, Daniel O’Nolan, Brennan Mcbride, Allison Wustrow, James R. Neilson, Karena W. Chapman, Qiang Du, Simon J. L. Billinge   +11 more
doaj   +3 more sources

Biclustering of gene expression data by non-smooth non-negative matrix factorization [PDF]

BMC Bioinformatics, 2006
Background The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of genes across tens or hundreds of different experimental conditions.
Carazo Jose M, Tirado F, Pascual-Marqui Roberto D, Carmona-Saez Pedro, Pascual-Montano Alberto   +4 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]

BMC 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

Link prediction based on non-negative matrix factorization. [PDF]

PLoS ONE, 2017
With the rapid expansion of internet, the complex networks has become high-dimensional, sparse and redundant. Besides, the problem of link prediction in such networks has also obatined increasingly attention from different types of domains like ...
Bolun Chen, Fenfen Li, Senbo Chen, Ronglin Hu, Ling Chen   +4 more
doaj   +4 more sources

Bayesian multi-study non-negative matrix factorization for mutational signatures [PDF]

Genome 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, Lorenzo Trippa, Giovanni Parmigiani   +2 more
doaj   +2 more sources

Fast optimization of non-negative matrix tri-factorization.

PLoS ONE, 2019
Non-negative matrix tri-factorization (NMTF) is a popular technique for learning low-dimensional feature representation of relational data. Currently, NMTF learns a representation of a dataset through an optimization procedure that typically uses ...
Andrej Čopar, Blaž Zupan, Marinka Zitnik   +2 more
doaj   +5 more sources