Exact Recovery of Community Detection in k-Community Gaussian Mixture Model
Social and Information Networks
2020-09-03 v1 Machine Learning
Probability
Machine Learning
Abstract
We study the community detection problem on a Gaussian mixture model, in which vertices are divided into distinct communities. The major difference in our model is that the intensities for Gaussian perturbations are different for different entries in the observation matrix, and we do not assume that every community has the same number of vertices. We explicitly find the threshold for the exact recovery of the maximum likelihood estimation. Applications include the community detection on hypergraphs.
Keywords
Cite
@article{arxiv.2009.01185,
title = {Exact Recovery of Community Detection in k-Community Gaussian Mixture Model},
author = {Zhongyang Li},
journal= {arXiv preprint arXiv:2009.01185},
year = {2020}
}