This contribution extends learning vector quantization to the domain of graphs. For this, we first identify graphs with points in some orbifold, then derive a generalized differentiable intrinsic metric, and finally extend the update rule of LVQ for generalized differentiable distance metrics. First experiments indicate that the proposed approach can perform comparable to state-of-the-art methods in structural pattern recognition.


Class Label Vector Representation Graph Match Graph Distance Optimal Alignment 
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 2010

Authors and Affiliations

  • Brijnesh J. Jain
    • 1
  • S. Deepak Srinivasan
    • 1
  • Alexander Tissen
    • 1
  • Klaus Obermayer
    • 1
  1. 1.Berlin Institute of TechnologyGermany

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