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Journal of Applied Nonlinear Dynamics 7(3) (2018) 269--285 | DOI:10.5890/JAND.2018.09.005

Filipe Alves Neto Verri$^{1}$,$^{2}$, Paulo Roberto Urio$^{3}$, Liang Zhao$^{4}$

$^{1}$ Institute of Mathematical and Computer Sciences, University of São Paulo, São Carlos, Brazil

$^{2}$ School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe AZ, USA

$^{3}$ Institute of Mathematical and Computer Sciences, University of São Paulo, São Carlos, Brazil

$^{4}$ Ribeir˜ao Preto School of Philosophy, Science and Literature, University of São Paulo, Ribeirão Preto, Brazil

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Abstract

We study how effectively edge-centric dynamics solve semi-supervised learning tasks. The Edge Domination System is an algorithm to reveal patterns and obtain information of the underlying complex network. The algorithm consists of the simulation of a collective dynamical system based on particle competition for the dominance of edges. In this paper, we propose a vertex-centric version of this model and assess the differences between the edge-centric model. The edge-centric system offers better features in semi-supervised learning tasks, such as greater exploration behavior and faster convergence.

Acknowledgments

This research was supported by the S˜ao Paulo State Research Foundation (FAPESP), the Coordination for the Improvement of Higher Education Personnel (CAPES), and the Brazilian National Research Council (CNPq).

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