Speeding up the dissimilarity self-organizing maps by branch and bound

Authors:
Brieuc Conan-Guez;Fabrice Rossi
Affiliations:
LITA EA, Université de Metz, Ile du Saulcy, Metz, France;INRIA, Le Chesnay Cedex, France
Venue:
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Year:
2007

Citing 3
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Abstract

This paper proposes to apply the branch and bound principle from combinatorial optimization to the Dissimilarity Self-Organizing Map (DSOM), a variant of the SOM that can handle dissimilarity data. A new reference model optimization method is derived from this principle. Its results are strictly identical to those of the original DSOM algorithm by Kohonen and Somervuo, while its running time is reduced by a factor up to 2.5 compared to the one of the previously proposed optimized implementation.