Variational Inference: Posterior Threshold Improves Network Clustering Accuracy in Sparse Regimes

arXiv:2301.04771v2 Announce Type: replace-cross
Abstract: Variational inference has been widely used in machine learning literature to fit various Bayesian models. In network analysis, this method has been successfully applied to solve the community detection problems. Although these results are promising, their theoretical support is only for relatively dense networks, an assumption that may not hold for real networks. In addition, it has been shown recently that the variational loss surface has many saddle points, which may severely affect its performance, …

abstract accuracy analysis arxiv bayesian clustering community cs.lg detection inference literature machine machine learning network networks posterior replace results solve stat.ml support threshold type