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International Conference on Artificial Neural Networks

ICANN 2011: Artificial Neural Networks and Machine Learning – ICANN 2011 pp 25–31Cite as

Transformation of Edge Weights in a Graph Bipartitioning Problem

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6792))

Abstract

In this paper we consider the problem of partitioning a graph into two parts of equal sizes with minimal sum of edge weights between them. It is known that this problem is NP-complete and can be reduced to the minimization of a quadratic binary functional with constraints. In previous work it was shown that raising the matrix of couplings to some power leads to a significant increase of the basin of attraction of the deepest functional minima. This means that such transformation possesses great optimizing abilities. In this paper we show that in spite of the constraints present in the graph bipartitioning problem, the proposed matrix transformation approach works very well with this problem.

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Author information

Authors and Affiliations

  1. Center of Optical and Neural Technologies of SRISA RAS, 119333, Moscow, Vavilova St., 44 b. 2, Russia

    I. M. Karandashev & B. V. Kryzhanovsky

Authors
  1. I. M. Karandashev
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  2. B. V. Kryzhanovsky
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Editor information

Editors and Affiliations

  1. Department of Information and Computer Science, Aalto University School of Science, P.O. Box 15400, 00076, Aalto, Finland

    Timo Honkela  & Samuel Kaski  & 

  2. School of Physics, Astronomy and Informatics, Department of Informatics, Nicolaus Copernicus University, ul. Grudziadzka 5, 87-100, Torun, Poland

    Włodzisław Duch

  3. Department of Statistical Science, University College London, 1-19 Torrington Place, WC1E 7HB, London, UK

    Mark Girolami

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© 2011 Springer-Verlag Berlin Heidelberg

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Karandashev, I.M., Kryzhanovsky, B.V. (2011). Transformation of Edge Weights in a Graph Bipartitioning Problem. In: Honkela, T., Duch, W., Girolami, M., Kaski, S. (eds) Artificial Neural Networks and Machine Learning – ICANN 2011. ICANN 2011. Lecture Notes in Computer Science, vol 6792. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21738-8_4

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  • DOI: https://doi.org/10.1007/978-3-642-21738-8_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21737-1

  • Online ISBN: 978-3-642-21738-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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