A0300
Title: Consistent community detection in inter-layer dependent multi-layer networks
Authors: Jingnan Zhang - University of Science and Technology of China (China) [presenting]
Abstract: Community detection in multi-layer networks, which aims at finding groups of nodes with similar connective patterns among all layers, has attracted tremendous interest in multi-layer network analysis. Most existing methods are extended from those for single-layer networks, which assume that different layers are independent. A novel community detection method is proposed in multi-layer networks with inter-layer dependence, which integrates the stochastic block model (SBM) and the Ising model. The SBM model models the community structure and the inter-layer dependence, which are incorporated via the Ising model. An efficient alternative updating algorithm is developed to tackle the resultant optimization task. Moreover, the asymptotic consistencies of the proposed method in terms of both parameter estimation and community detection are established, which are supported by extensive simulated examples and a real example of a multi-layer malaria parasite gene network.
