Riemannian preconditioning
Optimization and Control
2016-03-10 v3
Abstract
This paper exploits a basic connection between sequential quadratic programming and Riemannian gradient optimization to address the general question of selecting a metric in Riemannian optimization, in particular when the Riemannian structure is sought on a quotient manifold. The proposed method is shown to be particularly insightful and efficient in quadratic optimization with orthogonality and/or rank constraints, which covers most current applications of Riemannian optimization in matrix manifolds.
Cite
@article{arxiv.1405.6055,
title = {Riemannian preconditioning},
author = {Bamdev Mishra and Rodolphe Sepulchre},
journal= {arXiv preprint arXiv:1405.6055},
year = {2016}
}