• DocumentCode
    1452053
  • Title

    Dimensionality Reduction via Subspace and Submanifold Learning [From the Guest Editors]

  • Author

    Yi Ma ; Niyogi, P. ; Sapiro, Guillermo ; Vidal, Rene

  • Volume
    28
  • Issue
    2
  • fYear
    2011
  • fDate
    3/1/2011 12:00:00 AM
  • Firstpage
    14
  • Lastpage
    126
  • Abstract
    The featured articles cover very representative models and techniques that people have developed in recent years for modeling and extracting low-dimension al structures of high-dimensional data.
  • Keywords
    data handling; learning (artificial intelligence); dimensionality reduction; high-dimensional data; submanifold learning; subspace learning; Audio databases; Information analysis; Learning systems; Search problems; Special issues and sections; Web services;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2010.940005
  • Filename
    5714387
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1452053