Optimization and expansion of non-negative matrix factorization

Optimization and expansion of non-negative matrix factorization

Abstract Background Non-negative matrix factorization (NMF) is a technique widely used in various fields, including artificial intelligence (AI), signal processing and bioinformatics. However existing algorithms and R packages cannot be applied to large matrices due to their slow convergence or to m...

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Bibliographic Details
Main Authors: Xihui Lin, Paul C. Boutros
Format: Article
Language:English
Published: BMC 2020-01-01
Series:BMC Bioinformatics
Subjects:
Non-negative matrix factorization
Deconvolution
Imputation
Online Access:https://doi.org/10.1186/s12859-019-3312-5

Internet

https://doi.org/10.1186/s12859-019-3312-5

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