Learning graph quantization

Authors:
Brijnesh J. Jain;S. Deepak Srinivasan;Alexander Tissen;Klaus Obermayer
Affiliations:
Berlin Institute of Technology, Germany;Berlin Institute of Technology, Germany;Berlin Institute of Technology, Germany;Berlin Institute of Technology, Germany
Venue:
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Year:
2010

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Abstract

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.