Learning to Find Graph Pre-images

  • Gökhan H. Bakır
  • Alexander Zien
  • Koji Tsuda
Conference paper

DOI: 10.1007/978-3-540-28649-3_31

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3175)
Cite this paper as:
Bakır G.H., Zien A., Tsuda K. (2004) Learning to Find Graph Pre-images. In: Rasmussen C.E., Bülthoff H.H., Schölkopf B., Giese M.A. (eds) Pattern Recognition. DAGM 2004. Lecture Notes in Computer Science, vol 3175. Springer, Berlin, Heidelberg

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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