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Fast Population Game Dynamics for Dominant Sets and Other Quadratic Optimization Problems

  • Samuel Rota Bulò
  • Immanuel M. Bomze
  • Marcello Pelillo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6218)

Abstract

We propose a fast population game dynamics, motivated by the analogy with infection and immunization processes within a population of ”players,” for finding dominant sets, a powerful graph-theoretical notion of a cluster. Each step of the proposed dynamics is shown to have a linear time/space complexity and we show that, under the assumption of symmetric affinities, the average population payoff is strictly increasing along any non-constant trajectory, thereby allowing us to prove that dominant sets are asymptotically stable (i.e., attractive) points for the proposed dynamics. The approach is general and can be applied to a large class of quadratic optimization problems arising in computer vision. Experimentally, the proposed dynamics is found to be orders of magnitude faster than and as accurate as standard algorithms.

Keywords

Nash Equilibrium Image Segmentation Mixed Strategy Pure Strategy Image Match 
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

  • Samuel Rota Bulò
    • 1
  • Immanuel M. Bomze
    • 2
  • Marcello Pelillo
    • 1
  1. 1.Dipartimento di InformaticaUniv. of VeniceItaly
  2. 2.Department of Statistics and Decision Support SystemsUniv. of ViennaAustria

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