Manopt, a Matlab Toolbox for Optimization on Manifolds
Abstract
Optimization on manifolds is a rapidly developing branch of nonlinear optimization. Its focus is on problems where the smooth geometry of the search space can be leveraged to design efficient numerical algorithms. In particular, optimization on manifolds is well-suited to deal with rank and orthogonality constraints. Such structured constraints appear pervasively in machine learning applications, including low-rank matrix completion, sensor network localization, camera network registration, independent component analysis, metric learning, dimensionality reduction and so on.
Cite
Text
Boumal et al. "Manopt, a Matlab Toolbox for Optimization on Manifolds." Machine Learning Open Source Software, 2014.Markdown
[Boumal et al. "Manopt, a Matlab Toolbox for Optimization on Manifolds." Machine Learning Open Source Software, 2014.](https://mlanthology.org/mloss/2014/boumal2014jmlr-manopt/)BibTeX
@article{boumal2014jmlr-manopt,
title = {{Manopt, a Matlab Toolbox for Optimization on Manifolds}},
author = {Boumal, Nicolas and Mishra, Bamdev and Absil, P.-A. and Sepulchre, Rodolphe},
journal = {Machine Learning Open Source Software},
year = {2014},
pages = {1455-1459},
volume = {15},
url = {https://mlanthology.org/mloss/2014/boumal2014jmlr-manopt/}
}