A unified global convergence analysis of multiplicative update rules for nonnegative matrix factorization

DOI10.1007/s10589-018-9997-yzbMath1427.90269OpenAlexW2793316472MaRDI QIDQ1790683

Norikazu Takahashi, Masato Seki, Jun'ichi Takeuchi, Jiro Katayama

Publication date: 2 October 2018

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10589-018-9997-y

zbMATH Keywords

global convergencenonnegative matrix factorizationmultiplicative update rule

Mathematics Subject Classification ID

Analysis of algorithms (68W40) Factorization of matrices (15A23) Applications of mathematical programming (90C90) Nonlinear programming (90C30)

Related Items

A novel update rule of HALS algorithm for nonnegative matrix factorization and Zangwill's global convergence

Uses Software

• NeNMF

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Global convergence of modified multiplicative updates for nonnegative matrix factorization
• Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework
• A continuous characterization of the maximum-edge biclique problem
• Email surveillance using non-negative matrix factorization
• On the convergence properties of the EM algorithm
• Computing nonnegative rank factorizations
• The nonnegative rank factorizations of nonnegative matrices
• Nonnegative matrix factorization and I-divergence alternating minimization
• Document clustering using nonnegative matrix factorization
• Algorithms for Nonnegative Matrix Factorization with the β-Divergence
• Newton-based optimization for Kullback–Leibler nonnegative tensor factorizations
• On the Complexity of Nonnegative Matrix Factorization
• A Generalized Divergence Measure for Nonnegative Matrix Factorization
• Hierarchical ALS Algorithms for Nonnegative Matrix and 3D Tensor Factorization
• Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music Analysis
• Nonnegative Matrix Factorization Based on Alternating Nonnegativity Constrained Least Squares and Active Set Method
• NeNMF: An Optimal Gradient Method for Nonnegative Matrix Factorization
• On Tensors, Sparsity, and Nonnegative Factorizations
• Learning the parts of objects by non-negative matrix factorization
• Projected Gradient Methods for Nonnegative Matrix Factorization

This page was built for publication: A unified global convergence analysis of multiplicative update rules for nonnegative matrix factorization