5 papers
Attributed Network Alignment: Statistical Limits and Efficient Algorithm
Dong Huang, Chenyang Tian, Pengkun Yang
This paper studies the problem of recovering a hidden vertex correspondence between two correlated graphs when both edge weights and node features are observed. While most existing…
Fundamental Limits of Community Detection in Contextual Multi-Layer Stochastic Block Models
Shuyang Gong, Dong Huang, Zhangsong Li
We consider the problem of community detection from the joint observation of a high-dimensional covariate matrix and sparse networks, all encoding noisy, partial information ab…
Variational Estimators for Node Popularity Models
Jony Karki, Dongzhou Huang, Yunpeng Zhao
Node popularity is recognized as a key factor in modeling real-world networks, capturing heterogeneity in connectivity across communities. This concept is equally important in bipa…
Testing Correlation in Graphs by Counting Bounded Degree Motifs
Dong Huang, Pengkun Yang
We investigate the problem of detecting correlation between two Erdős-Rényi graphs , formulated as a hypothesis testing problem: under the null hypothesis, the two graphs a…
Sample Complexity of Correlation Detection in the Gaussian Wigner Model
Dong Huang, Pengkun Yang
Correlation analysis is a fundamental step in uncovering meaningful insights from complex datasets. In this paper, we study the problem of detecting correlations between two random…