Releases · rikenbit/OnlineNMF.jl

15 Jan 00:00

v0.99.8

1c6c167

OnlineNMF.jl: A Julia Package for Out-of-core and Sparse Non-negative Matrix Factorization Latest

Latest

Peer-reviewed software and manuscript. See the JOSS review issue for details:
openjournals/joss-reviews#9293

Non-negative Matrix Factorization (NMF) is a widely used dimensionality reduction technique for identifying a small number of non-negative components that minimize the reconstruction error when applied to high-dimensional data. NMF has been applied across various fields of data science, including face recognition, audio signal processing, recommender system, natural language processing (also known as a "topic model"), population genetics (also known as "admixture analysis"), and omics studies.

Despite its broad applicability, NMF becomes computationally prohibitive for large data matrices, making it difficult to apply in practice. In particular, recent advances in single-cell omics have led to datasets with millions of cells, for which standard NMF implementations often fail to scale. To meet this requirement, I present OnlineNMF.jl, which is a Julia package to perform some NMF algorithms (https://github.com/rikenbit/OnlineNMF.jl).

Zenodo doi: 10.5281/zenodo.18250632

Assets 2