View in EDS

Manopt, a Matlab Toolbox for Optimization on Manifolds.

Saved in:
Bibliographic Details
Title: Manopt, a Matlab Toolbox for Optimization on Manifolds.
Authors: Boumal, Nicolas1 NICOLASBOUMAL@GMAIL.COM, Mishra, Bamdev2 BAMDEVM@GMAIL.COM, Absil, P. A.1 ABSIL@INMA.UCL.AC.BE, Sepulchre, Rodolphe3 R.SEPULCHRE@ENG.CAM.AC.UK
Source: Journal of Machine Learning Research. 2014, Vol. 15 Issue 4, p1455-1459. 5p.
Subjects: MatLab (Computer software), Mathematical optimization, Manifolds (Mathematics), Nonlinear theories, Algorithms, Machine learning
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. The Manopt toolbox, available at www.manopt.org, is a user-friendly, documented piece of software dedicated to simplify experimenting with state of the art Riemannian optimization algorithms. By dealing internally with most of the differential geometry, the package aims particularly at lowering the entrance barrier. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Machine Learning Research is the property of Microtome Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 96263424
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Manopt, a Matlab Toolbox for Optimization on Manifolds.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Boumal%2C+Nicolas%22">Boumal, Nicolas</searchLink><relatesTo>1</relatesTo><i> NICOLASBOUMAL@GMAIL.COM</i><br /><searchLink fieldCode="AR" term="%22Mishra%2C+Bamdev%22">Mishra, Bamdev</searchLink><relatesTo>2</relatesTo><i> BAMDEVM@GMAIL.COM</i><br /><searchLink fieldCode="AR" term="%22Absil%2C+P%2E+A%2E%22">Absil, P. A.</searchLink><relatesTo>1</relatesTo><i> ABSIL@INMA.UCL.AC.BE</i><br /><searchLink fieldCode="AR" term="%22Sepulchre%2C+Rodolphe%22">Sepulchre, Rodolphe</searchLink><relatesTo>3</relatesTo><i> R.SEPULCHRE@ENG.CAM.AC.UK</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Journal+of+Machine+Learning+Research%22">Journal of Machine Learning Research</searchLink>. 2014, Vol. 15 Issue 4, p1455-1459. 5p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22MatLab+%28Computer+software%29%22">MatLab (Computer software)</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Manifolds+%28Mathematics%29%22">Manifolds (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22Nonlinear+theories%22">Nonlinear theories</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. The Manopt toolbox, available at www.manopt.org, is a user-friendly, documented piece of software dedicated to simplify experimenting with state of the art Riemannian optimization algorithms. By dealing internally with most of the differential geometry, the package aims particularly at lowering the entrance barrier. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Machine Learning Research is the property of Microtome Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=96263424
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 5
        StartPage: 1455
    Subjects:
      – SubjectFull: MatLab (Computer software)
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Manifolds (Mathematics)
        Type: general
      – SubjectFull: Nonlinear theories
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Machine learning
        Type: general
    Titles:
      – TitleFull: Manopt, a Matlab Toolbox for Optimization on Manifolds.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Boumal, Nicolas
      – PersonEntity:
          Name:
            NameFull: Mishra, Bamdev
      – PersonEntity:
          Name:
            NameFull: Absil, P. A.
      – PersonEntity:
          Name:
            NameFull: Sepulchre, Rodolphe
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 04
              Text: 2014
              Type: published
              Y: 2014
          Identifiers:
            – Type: issn-print
              Value: 15324435
          Numbering:
            – Type: volume
              Value: 15
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Journal of Machine Learning Research
              Type: main
ResultId 1