Approximate matrix and tensor diagonalization by unitary transformations: convergence of Jacobi-type algorithms
Optimization and Control
2020-07-13 v3 Numerical Analysis
Numerical Analysis
Abstract
We propose a gradient-based Jacobi algorithm for a class of maximization problems on the unitary group, with a focus on approximate diagonalization of complex matrices and tensors by unitary transformations. We provide weak convergence results, and prove local linear convergence of this algorithm.The convergence results also apply to the case of real-valued tensors.
Cite
@article{arxiv.1905.12295,
title = {Approximate matrix and tensor diagonalization by unitary transformations: convergence of Jacobi-type algorithms},
author = {Konstantin Usevich and Jianze Li and Pierre Comon},
journal= {arXiv preprint arXiv:1905.12295},
year = {2020}
}