论文标题
精确恢复K-Community高斯混合模型中的社区检测
Exact Recovery of Community Detection in k-Community Gaussian Mixture Model
论文作者
论文摘要
我们在高斯混合模型上研究社区检测问题，其中顶点分为$ k \ geq 2 $不同的社区。我们模型的主要区别在于，在观察矩阵中的不同条目中，高斯扰动的强度有所不同，我们并不认为每个社区都有相同数量的顶点。我们明确地找到了最大似然估计的精确恢复的阈值。应用程序包括有关超图的社区检测。
We study the community detection problem on a Gaussian mixture model, in which vertices are divided into $k\geq 2$ 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.
