IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v29y2014i3p569-590.html
   My bibliography  Save this article

Two Newton methods on the manifold of fixed-rank matrices endowed with Riemannian quotient geometries

Author

Listed:
  • P.-A. Absil
  • Luca Amodei
  • Gilles Meyer

Abstract

We consider two Riemannian geometries for the manifold $${\mathcal{M }(p,m\times n)}$$ M ( p , m × n ) of all $$m\times n$$ m × n matrices of rank $$p$$ p . The geometries are induced on $${\mathcal{M }(p,m\times n)}$$ M ( p , m × n ) by viewing it as the base manifold of the submersion $$\pi :(M,N)\mapsto MN^\mathrm{T}$$ π : ( M , N ) ↦ M N T , selecting an adequate Riemannian metric on the total space, and turning $$\pi $$ π into a Riemannian submersion. The theory of Riemannian submersions, an important tool in Riemannian geometry, makes it possible to obtain expressions for fundamental geometric objects on $${\mathcal{M }(p,m\times n)}$$ M ( p , m × n ) and to formulate the Riemannian Newton methods on $${\mathcal{M }(p,m\times n)}$$ M ( p , m × n ) induced by these two geometries. The Riemannian Newton methods admit a stronger and more streamlined convergence analysis than the Euclidean counterpart, and the computational overhead due to the Riemannian geometric machinery is shown to be mild. Potential applications include low-rank matrix completion and other low-rank matrix approximation problems. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • P.-A. Absil & Luca Amodei & Gilles Meyer, 2014. "Two Newton methods on the manifold of fixed-rank matrices endowed with Riemannian quotient geometries," Computational Statistics, Springer, vol. 29(3), pages 569-590, June.
  • Handle: RePEc:spr:compst:v:29:y:2014:i:3:p:569-590
    DOI: 10.1007/s00180-013-0441-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00180-013-0441-6
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s00180-013-0441-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nickolay Trendafilov & Martin Kleinsteuber & Hui Zou, 2014. "Sparse matrices in data analysis," Computational Statistics, Springer, vol. 29(3), pages 403-405, June.
    2. P.-A. Absil & I. Oseledets, 2015. "Low-rank retractions: a survey and new results," Computational Optimization and Applications, Springer, vol. 62(1), pages 5-29, September.
    3. Teles A. Fernandes & Orizon P. Ferreira & Jinyun Yuan, 2017. "On the Superlinear Convergence of Newton’s Method on Riemannian Manifolds," Journal of Optimization Theory and Applications, Springer, vol. 173(3), pages 828-843, June.
    4. T. Bittencourt & O. P. Ferreira, 2017. "Kantorovich’s theorem on Newton’s method under majorant condition in Riemannian manifolds," Journal of Global Optimization, Springer, vol. 68(2), pages 387-411, June.
    5. Marcio Antônio de A. Bortoloti & Teles A. Fernandes & Orizon P. Ferreira & Jinyun Yuan, 2020. "Damped Newton’s method on Riemannian manifolds," Journal of Global Optimization, Springer, vol. 77(3), pages 643-660, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:compst:v:29:y:2014:i:3:p:569-590. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.