Spectral clustering via adaptive layer aggregation for multi-layer networks. (arXiv:2012.04646v2 [stat.ML] UPDATED)

One of the fundamental problems in network analysis is detecting community
structure in multi-layer networks, of which each layer represents one type of
edge information among the nodes. We propose integrative spectral clustering
approaches based on effective convex layer aggregations. Our aggregation
methods are strongly motivated by a delicate asymptotic analysis of the
spectral embedding of weighted adjacency matrices and the downstream $k$-means
clustering, in a challenging regime where community detection consistency is
impossible. In fact, the methods are shown …

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