# Exact Recovery of Community Detection in k-Community Gaussian Mixture Model

arXiv: https://arxiv.org/abs/2009.01185 · HTML: https://mlsanity.com/paper/2009.01185/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Aug 2020.

## Built on by (most cited first, 3 of 3)

- [Exact Recovery of Community Detection in dependent Gaussian Mixture Models](https://mlsanity.com/paper/2209.14859/) (2022)
- [Individual-heterogeneous sub-Gaussian Mixture Models](https://mlsanity.com/paper/2604.05337/) (2026)
- [Fast estimation of Gaussian mixture components via centering and singular value thresholding](https://mlsanity.com/paper/2604.19091/) (2026)

## Abstract (arXiv)

We study the community detection problem on a Gaussian mixture model, in which vertices are divided into k≥ 2 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.