• DocumentCode
    1186193
  • Title

    Deterministic Column-Based Matrix Decomposition

  • Author

    Li, Xuelong ; Pang, Yanwei

  • Author_Institution
    State Key Lab. of Transient Opt. & Photonics, Chinese Acad. of Sci., Xi´´an, China
  • Volume
    22
  • Issue
    1
  • fYear
    2010
  • Firstpage
    145
  • Lastpage
    149
  • Abstract
    In this paper, we propose a deterministic column-based matrix decomposition method. Conventional column-based matrix decomposition (CX) computes the columns by randomly sampling columns of the data matrix. Instead, the newly proposed method (termed as CX_D) selects columns in a deterministic manner, which well approximates singular value decomposition. The experimental results well demonstrate the power and the advantages of the proposed method upon three real-world data sets.
  • Keywords
    data mining; learning (artificial intelligence); sampling methods; singular value decomposition; data matrix training; data mining; deterministic column-based matrix decomposition; random data matrix sampling; singular value decomposition; Matrix decomposition; dimensionality reduction.; feature extraction; incremental learning;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/TKDE.2009.64
  • Filename
    4798166
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1186193