3 citations · 8 across the 9 of their papers we have counts for
11 papers
Information-theoretic Limits for Testing Community Structures in Weighted Networks
Mingao Yuan, Zuofeng Shang
Community detection refers to the problem of clustering the nodes of a network into groups. Existing inferential methods for community structure mainly focus on unweighted (binary)…
Statistical Limits for Testing Correlation of Hypergraphs
Mingao Yuan, Zuofeng Shang
In this paper, we consider the hypothesis testing of correlation between two -uniform hypergraphs on unlabelled nodes. Under the null hypothesis, the hypergraphs are indepen…
Community detection in censored hypergraph
Mingao Yuan, Bin Zhao, Xiaofeng Zhao
Community detection refers to the problem of clustering the nodes of a network (either graph or hypergrah) into groups. Various algorithms are available for community detection and…
Information Limits for Detecting a Subhypergraph
Mingao Yuan, Zuofeng Shang
We consider the problem of recovering a subhypergraph based on an observed adjacency tensor corresponding to a uniform hypergraph. The uniform hypergraph is assumed to contain a su…
Heterogeneous Dense Subhypergraph Detection
Mingao Yuan, Zuofeng Shang
We study the problem of testing the existence of a heterogeneous dense subhypergraph. The null hypothesis corresponds to a heterogeneous Erdös-Rényi uniform random hypergraph and t…
A Practical Two-Sample Test for Weighted Random Graphs
Mingao Yuan, Qian Wen
Network (graph) data analysis is a popular research topic in statistics and machine learning. In application, one is frequently confronted with graph two-sample hypothesis testing…