A Hybrid Penalty Method for a Class of Optimization Problems with Multiple Rank Constraints

DOI10.1137/19M1269919zbMath1462.90128arXiv1906.10396OpenAlexW3082992513MaRDI QIDQ5146698

Akiko Takeda, Ting Kei Pong, Ivan Markovsky, Tianxiang Liu

Publication date: 26 January 2021

Published in: SIAM Journal on Matrix Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1906.10396

zbMATH Keywords

system identificationHankel structurepseudoprojectionhybrid penalty method

Mathematics Subject Classification ID

Nonlinear programming (90C30)

Related Items (1)

Normal Cones Intersection Rule and Optimality Analysis for Low-Rank Matrix Optimization with Affine Manifolds

Uses Software

• SLRA

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Overview of total least-squares methods
• Local linear convergence for alternating and averaged nonconvex projections
• Common pole estimation in multi-channel exponential data modeling
• On approximate GCDs of univariate polynomials
• Low-rank approximation. Algorithms, implementation, applications
• Prox-regularity of rank constraint sets and implications for algorithms
• Variable projection for affinely structured low-rank approximation in weighted \(2\)-norms
• Software for weighted structured low-rank approximation
• Variable projection methods for approximate (greatest) common divisor computations
• A successive difference-of-convex approximation method for a class of nonconvex nonsmooth optimization problems
• Structured low-rank approximation and its applications
• Structured Low-Rank Approximation with Missing Data
• Factorization Approach to Structured Low-Rank Approximation with Applications
• Variational Analysis
• Sparse Reconstruction by Separable Approximation
• On the Low-Rank Approximation of Data on the Unit Sphere

This page was built for publication: A Hybrid Penalty Method for a Class of Optimization Problems with Multiple Rank Constraints