dc.contributor.author | Bergmann, Ronny | |
dc.date.accessioned | 2023-03-07T19:55:19Z | |
dc.date.available | 2023-03-07T19:55:19Z | |
dc.date.created | 2022-02-11T07:22:41Z | |
dc.date.issued | 2022 | |
dc.identifier.issn | 2475-9066 | |
dc.identifier.uri | https://hdl.handle.net/11250/3056874 | |
dc.description.abstract | Manopt.jl provides a set of optimization algorithms for optimization problems given on a Riemannian manifold M. Based on a generic optimization framework, together with the interface ManifoldsBase.jl for Riemannian manifolds, classical and recently developed methods are provided in an efficient implementation. Algorithms include the derivative-free Particle Swarm and Nelder–Mead algorithms, as well as classical gradient, conjugate gradient and stochastic gradient descent. Furthermore, quasi-Newton methods like a Riemannian L-BFGS and nonsmooth optimization algorithms like a Cyclic Proximal Point Algorithm, a (parallel) Douglas-Rachford algorithm and a Chambolle-Pock algorithm are provided, together with several basic cost functions, gradients and proximal maps as well as debug and record capabilities. | en_US |
dc.description.abstract | Manopt.jl: Optimization on Manifolds in Julia | en_US |
dc.language.iso | eng | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Manopt.jl: Optimization on Manifolds in Julia | en_US |
dc.title.alternative | Manopt.jl: Optimization on Manifolds in Julia | en_US |
dc.type | Journal article | en_US |
dc.type | Peer reviewed | en_US |
dc.description.version | publishedVersion | en_US |
dc.source.volume | 7 | en_US |
dc.source.journal | Journal of Open Source Software (JOSS) | en_US |
dc.identifier.doi | 10.21105/joss.03866 | |
dc.identifier.cristin | 2000275 | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |