scientific article; zbMATH DE number 7569347
From MaRDI portal
Publication:5095420
DOI10.12941/jksiam.2021.25.107zbMath1497.15016MaRDI QIDQ5095420
Publication date: 8 August 2022
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
block coordinate descentBregman distancenon-negative matrix factorisationBregman proximal gradientmajorization and minimization
Factorization of matrices (15A23) Numerical optimization and variational techniques (65K10) Norms of matrices, numerical range, applications of functional analysis to matrix theory (15A60) Direct numerical methods for linear systems and matrix inversion (65F05)
Related Items (1)
Uses Software
Cites Work
- A column-wise update algorithm for nonnegative matrix factorization in Bregman divergence with an orthogonal constraint
- Families of alpha-, beta- and gamma-divergences: flexible and robust measures of similarities
- Surrogate maximization/minimization algorithms and extensions
- Inertial proximal gradient methods with Bregman regularization for a class of nonconvex optimization problems
- Algorithms for nonnegative matrix factorization with the Kullback-Leibler divergence
- Multi-block Bregman proximal alternating linearized minimization and its application to orthogonal nonnegative matrix factorization
- A block inertial Bregman proximal algorithm for nonsmooth nonconvex problems with application to symmetric nonnegative matrix tri-factorization
- Algorithms for Nonnegative Matrix Factorization with the β-Divergence
- Hierarchical ALS Algorithms for Nonnegative Matrix and 3D Tensor Factorization
- Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music Analysis
- First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems
- Relatively Smooth Convex Optimization by First-Order Methods, and Applications
- TYPE II TOPP-LEONE INVERSE WEIBULL DISTRIBUTION WITH STATISTICAL PROPERTIES AND APPLICATIONS
- Proximal Distance Algorithms: Theory and Examples
- A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications
- Independent Component Analysis and Blind Signal Separation
This page was built for publication: