• DocumentCode
    2373253
  • Title

    Convergence-guaranteed multiplicative algorithms for nonnegative matrix factorization with β-divergence

  • Author

    Nakano, Masahiro ; Kameoka, Hirokazu ; Le Roux, Jonathan ; Kitano, Yu. ; Ono, Nobutaka ; Sagayama, Shigeki

  • Author_Institution
    Grad. Sch. of Inf. Sci. & Technol., Univ. of Tokyo, Tokyo, Japan
  • fYear
    2010
  • fDate
    Aug. 29 2010-Sept. 1 2010
  • Firstpage
    283
  • Lastpage
    288
  • Abstract
    This paper presents a new multiplicative algorithm for nonnegative matrix factorization with β-divergence. The derived update rules have a similar form to those of the conventional multiplicative algorithm, only differing through the presence of an exponent term depending on β. The convergence is theoretically proven for any real-valued β based on the auxiliary function method. The convergence speed is experimentally investigated in comparison with previous works.
  • Keywords
    convergence; matrix decomposition; matrix multiplication; β-divergence; convergence-guaranteed multiplicative algorithms; nonnegative matrix factorization; Book reviews; Convergence; Maximum likelihood estimation; Minimization; Signal processing algorithms; Source separation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop on
  • Conference_Location
    Kittila
  • ISSN
    1551-2541
  • Print_ISBN
    978-1-4244-7875-0
  • Electronic_ISBN
    1551-2541
  • Type

    conf

  • DOI
    10.1109/MLSP.2010.5589233
  • Filename
    5589233