• DocumentCode
    2919395
  • Title

    MKPM: A multiclass extension to the kernel projection machine

  • Author

    Takerkart, Sylvain ; Ralaivola, Liva

  • Author_Institution
    Inst. de Neurosciences Cognitives de la Mediterranee, Aix-Marseille Univ., Marseille, France
  • fYear
    2011
  • fDate
    20-25 June 2011
  • Firstpage
    2785
  • Lastpage
    2791
  • Abstract
    We introduce Multiclass Kernel Projection Machines (MKPM), a new formalism that extends the Kernel Projection Machine framework to the multiclass case. Our formulation is based on the use of output codes and it implements a co-regularization scheme by simultaneously constraining the projection dimensions associated with the individual predictors that constitute the global classifier. In order to solve the optimization problem posed by our formulation, we propose an efficient dynamic programming approach. Numerical simulations conducted on a few pattern recognition problems illustrate the soundness of our approach.
  • Keywords
    dynamic programming; pattern classification; MKPM; dynamic programming approach; multiclass extension; multiclass kernel projection machine; optimization problem; pattern recognition problem; Dynamic programming; Encoding; Kernel; Machine learning; Minimization; Numerical simulation; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on
  • Conference_Location
    Providence, RI
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4577-0394-2
  • Type

    conf

  • DOI
    10.1109/CVPR.2011.5995657
  • Filename
    5995657