L2-SVM Training with Distributed Data

  • Stefano Lodi
  • Ricardo Ñanculef
  • Claudio Sartori
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5774)


We propose an algorithm for the problem of training a SVM model when the set of training examples is horizontally distributed across several data sources. The algorithm requires only one pass through each remote source of training examples, and its accuracy and efficiency follow a clear pattern as function of a user-defined parameter. We outline an agent-based implementation of the algorithm.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Stefano Lodi
    • 1
  • Ricardo Ñanculef
    • 2
  • Claudio Sartori
    • 1
  1. 1.Dept. of Electronics, Comp. Sc. and SystemsUniversity of BolognaItaly
  2. 2.Department of InformaticsFederico Santa María UniversityChile

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