Divergence Functions of Non negative Matrix Factorization: A Comparison Study

DOI10.1080/03610918.2011.589734zbMath1227.62003OpenAlexW2037001019MaRDI QIDQ3102908

Zhong-Yuan Zhang

Publication date: 25 November 2011

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2011.589734

zbMATH Keywords

clusteringimage processingblind source separation

Mathematics Subject Classification ID

Factorization of matrices (15A23) Applications of mathematical programming (90C90) Nonlinear programming (90C30) Learning and adaptive systems in artificial intelligence (68T05) Statistical aspects of information-theoretic topics (62B10)

Related Items (1)

Accelerated parallel and distributed algorithm using limited internal memory for nonnegative matrix factorization

Uses Software

• NMFLAB

Cites Work

• Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music Analysis
• Learning the parts of objects by non-negative matrix factorization
• Independent Component Analysis and Blind Signal Separation

This page was built for publication: Divergence Functions of Non negative Matrix Factorization: A Comparison Study