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Bio-inspired dynamical processes are able to identify nonlinear features in data. We present a dynamical process model of particle competition in complex networks applied to transductive semi-supervised learning. Particles carry labels and compete for the domination of edges. The process results consist of sets of edges arranged by label dominance. The sets are analyzed as subnetworks for the data...
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