Learning to Find Graph Pre-images

  • Gökhan H. Bakır
  • Alexander Zien
  • Koji Tsuda
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3175)

Abstract

The recent development of graph kernel functions has made it possible to apply well-established machine learning methods to graphs. However, to allow for analyses that yield a graph as a result, it is necessary to solve the so-called pre-image problem: to reconstruct a graph from its feature space representation induced by the kernel. Here, we suggest a practical solution to this problem.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Gökhan H. Bakır
    • 1
  • Alexander Zien
    • 1
  • Koji Tsuda
    • 1
    • 2
  1. 1.Max Planck Institute for Biological Cybernetics, Dept. SchölkopfTübingenGermany
  2. 2.AIST Computational Biology Research CenterTokyoJapan

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