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The Huller: A Simple and Efficient Online SVM

  • Antoine Bordes
  • Léon Bottou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3720)

Abstract

We propose a novel online kernel classifier algorithm that converges to the Hard Margin SVM solution. The same update rule is used to both add and remove support vectors from the current classifier. Experiments suggest that this algorithm matches the SVM accuracies after a single pass over the training examples. This algorithm is attractive when one seeks a competitive classifier with large datasets and limited computing resources.

Keywords

Support Vector Machine Support Vector Online Algorithm Cache Size Machine Learn Research 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Antoine Bordes
    • 1
    • 2
  • Léon Bottou
    • 2
  1. 1.Ecole Supérieure de Physique et de Chimie IndustriellesParisFrance
  2. 2.NEC Labs AmericaPrincetonUSA

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