Exact Solutions in Structured Low-Rank Approximation
Optimization and Control
2017-02-23 v3 Symbolic Computation
Algebraic Geometry
Computation
Abstract
Structured low-rank approximation is the problem of minimizing a weighted Frobenius distance to a given matrix among all matrices of fixed rank in a linear space of matrices. We study exact solutions to this problem by way of computational algebraic geometry. A particular focus lies on Hankel matrices, Sylvester matrices and generic linear spaces.
Cite
@article{arxiv.1311.2376,
title = {Exact Solutions in Structured Low-Rank Approximation},
author = {Giorgio Ottaviani and Pierre-Jean Spaenlehauer and Bernd Sturmfels},
journal= {arXiv preprint arXiv:1311.2376},
year = {2017}
}
Comments
22 pages; theorem numbering fits with the journal version