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This paper is related to community detection in complex networks. We show the use of kernel spectral clustering for the analysis of unweighted networks. We employ the primaldual framework and make use of out-of-sample extensions. In particular, we propose a method to extract from a network a small subgraph representative for its overall community structure. We use a model selection procedure based on the modularity statistic which is novel, because modularity is commonly used only at a trainingdoi:10.1109/ijcnn.2012.6252726 dblp:conf/ijcnn/LangoneAS12 fatcat:vtzvesp3nvetppawtxcrrntqpm