IDEAS home Printed from https://ideas.repec.org/a/spr/coopap/v88y2024i3d10.1007_s10589-024-00574-8.html
   My bibliography  Save this article

An inexactly accelerated algorithm for nonnegative tensor CP decomposition with the column unit constraints

Author

Listed:
  • Zihao Wang

    (Hunan University)

  • Minru Bai

    (Hunan University)

Abstract

The component separation problem in complex chemical systems is very important and challenging in chemometrics. In this paper, we study a third-order nonnegative CANDECOMP/PARAFAC decomposition model with the column unit constraints (NCPD_CU) motivated by the component separation problem. To solve the NCPD_CU model, we first explore rapid computational methods for a generalized class of three-block optimization problems, which may exhibit nonconvexity and nonsmoothness. To this end, we propose the accelerated inexact block coordinate descent (AIBCD) algorithm, where each subproblem is inexactly solved through a finite number of inner-iterations employing the alternating proximal gradient method. Additionally, the algorithm incorporates extrapolation during the outer-iterations to enhance overall efficiency. We prove that the iterative sequence generated by the algorithm converges to a stationary point under mild conditions. Subsequently, we apply this methodology to the NCPD_CU model that satisfies the specified conditions. Finally, we present numerical results using both synthetic and real-world data, showcasing the remarkable efficiency of our proposed method.

Suggested Citation

  • Zihao Wang & Minru Bai, 2024. "An inexactly accelerated algorithm for nonnegative tensor CP decomposition with the column unit constraints," Computational Optimization and Applications, Springer, vol. 88(3), pages 923-962, July.
  • Handle: RePEc:spr:coopap:v:88:y:2024:i:3:d:10.1007_s10589-024-00574-8
    DOI: 10.1007/s10589-024-00574-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10589-024-00574-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10589-024-00574-8?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.

    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:coopap:v:88:y:2024:i:3:d:10.1007_s10589-024-00574-8. 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.