arXiv:2101.02307v4 Announce Type: replace-cross
Abstract: Mixed membership modeling for undirected networks has been extensively explored in network science over the past few years. Despite the subst...
By Huan Qing, Jingli Wang
The paper introduces a degree‑corrected joint matrix factorization technique for detecting communities in multilayer networks. It uses a nonnegative symmetric matrix trifactorization that enforces disjoint, shared communities across layers while allowing each layer to have distinct connectivity patterns and node degrees. An efficient algorithm is presented and evaluated on a multilayer degree‑corrected stochastic block model, showing superior performance compared to existing methods.
By Alexandra Dache, Manon Rustin, Arnaud Vandaele, Nicolas Gillis
arXiv:2609.12445v1 Announce Type: cross
Abstract: Community detection in bipartite networks is a fundamental problem in modern data analysis, with applications in recommendation systems, biological n...
By Huan Qing
arXiv:2608. 11321v1 Announce Type: cross Abstract: We study spectral clustering in the presence of a confounding latent geometry.
By Konstantin Avrachenkov, Lucas S. Sibemberg, Alexander Van Werde
arXiv:2608. 10845v1 Announce Type: cross Abstract: Spectral clustering methods for network data are commonly based on a few matrix representations, such as the adjacency matrix and the symmetric Laplacian.
By John Park, Ning Hao
arXiv:2606. 09100v1 Announce Type: cross Abstract: Community detection is a fundamental problem in the analysis of complex networks.
By Shahin Momenzadeh, Rojiar Pir Mohammadiani