Identification of network modules by optimization of ratio association.

@article{Angelini2007IdentificationON,
  title={Identification of network modules by optimization of ratio association.},
  author={L Angelini and Stefano Boccaletti and Daniele Marinazzo and Mario Pellicoro and Sebastiano Stramaglia},
  journal={Chaos},
  year={2007},
  volume={17 2},
  pages={023114}
}
We introduce a novel method for identifying the modular structures of a network based on the maximization of an objective function: the ratio association. This cost function arises when the communities detection problem is described in the probabilistic autoencoder frame. An analogy with kernel k-means methods allows us to develop an efficient optimization algorithm, based on the deterministic annealing scheme. The performance of the proposed method is shown on real data sets and on simulated… CONTINUE READING
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