9 citations · 19 across the 14 of their papers we have counts for
14 papers
Empirical likelihood test for community structure in networks
Mingao Yuan, Sharmin Hossain, Zuofeng Shang
Network data, characterized by interconnected nodes and edges, is pervasive in various domains and has gained significant popularity in recent years. In network data analysis, test…
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…
Online Statistical Inference for Parameters Estimation with Linear-Equality Constraints
Ruiqi Liu, Mingao Yuan, Zuofeng Shang
Stochastic gradient descent (SGD) and projected stochastic gradient descent (PSGD) are scalable algorithms to compute model parameters in unconstrained and constrained optimization…
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…
A practical test for a planted community in heterogeneous networks
Mingao Yuan, Qian Wen
One of the fundamental task in graph data mining is to find a planted community(dense subgraph), which has wide application in biology, finance, spam detection and so on. For a rea…
Sharp detection boundaries on testing dense subhypergraph
Mingao Yuan, Zuofeng Shang
We study the problem of testing the existence of a dense subhypergraph. The null hypothesis is an Erdos-Renyi uniform random hypergraph and the alternative hypothesis is a uniform…
On the geometric structure ofsome statistical manifolds
Mingao Yuan
In information geometry, one of the basic problem is to study the geomet-ric properties of statistical manifold. In this paper, we study the geometricstructure of the generalized n…
Testing Community Structures for Hypergraphs
Mingao Yuan, Ruiqi Liu, Yang Feng +1
Many complex networks in real world can be formulated as hypergraphs where community detection has been widely used. However, the fundamental question of whether communities exist…
A likelihood-ratio type test for stochastic block models with bounded degrees
Mingao Yuan, Yang Feng, Zuofeng Shang
A fundamental problem in network data analysis is to test Erdös-Rényi model versus a bisection stochastic block model $\mathcal{G}\left(n…
Empirical likelihood inference for partial functional linear regression models based on B spline
Mingao Yuan, Yue Zhang
In this paper, we apply empirical likelihood method to inference for the regression parameters in the partial functional linear regression models based on B spline. We prove that t…