• DocumentCode
    2210436
  • Title

    Compressed Nonnegative Sparse Coding

  • Author

    Wang, Fei ; Li, Ping

  • Author_Institution
    Dept. of Stat. Sci., Cornell Univ., Ithaca, NY, USA
  • fYear
    2010
  • fDate
    13-17 Dec. 2010
  • Firstpage
    1103
  • Lastpage
    1108
  • Abstract
    Sparse Coding (SC), which models the data vectors as sparse linear combinations over basis vectors, has been widely applied in machine learning, signal processing and neuroscience. In this paper, we propose a dual random projection method to provide an efficient solution to Nonnegative Sparse Coding (NSC) using small memory. Experiments on real world data demonstrate the effectiveness of the proposed method.
  • Keywords
    data reduction; matrix decomposition; source coding; vectors; Nonnegative Sparse Coding; data vector; dual random projection method; sparse linear combination;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining (ICDM), 2010 IEEE 10th International Conference on
  • Conference_Location
    Sydney, NSW
  • ISSN
    1550-4786
  • Print_ISBN
    978-1-4244-9131-5
  • Electronic_ISBN
    1550-4786
  • Type

    conf

  • DOI
    10.1109/ICDM.2010.162
  • Filename
    5694092
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2210436