Scalable non-negative matrix tri-factorization

Abstract 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. Matrix factorization learns a latent data model...

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Hauptverfasser: Andrej Čopar, Marinka žitnik, Blaž Zupan
Format: Artigo
Sprache:Inglês
Veröffentlicht: BMC 2017-12-01
Schriftenreihe:BioData Mining
Schlagworte:
Matrix factorization
Non-negative matrix tri-factorization
Non-negative block value decomposition
Block-wise multiplication
Graphics-processing unit
Large scale latent factor analysis
Online Zugang:http://link.springer.com/article/10.1186/s13040-017-0160-6
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