• DocumentCode
    3130304
  • Title

    Understanding and Exploiting the Connections between NMF and SVM

  • Author

    Potluru, Vamsi K.

  • Author_Institution
    Dept. of Comput. Sci., Univ. of New Mexico, Albuquerque, NM, USA
  • fYear
    2011
  • fDate
    11-11 Dec. 2011
  • Firstpage
    1207
  • Lastpage
    1210
  • Abstract
    Support Vector Machines (SVM) and Nonnegative Matrix Factorization (NMF) are standard tools for data analysis. We explore the connections between these two problems, thereby enabling us to import algorithms from SVM world to solve NMF and vice-versa. In particular, one such algorithm developed to solve SVM is adapted to solve NMF. Empirical results show that this new algorithm is competitive with the state-of-the-art NMF solvers.
  • Keywords
    matrix decomposition; support vector machines; NMF; SVM; data analysis; nonnegative matrix factorization; support vector machine; Data mining; Face; Kernel; Machine learning; Optimization; Support vector machines; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    978-1-4673-0005-6
  • Type

    conf

  • DOI
    10.1109/ICDMW.2011.172
  • Filename
    6137519
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3130304