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Found 9 papers, 0 papers with code
Statistical Limits for Testing Correlation of Hypergraphs
In this paper, we consider the hypothesis testing of correlation between two $m$-uniform hypergraphs on $n$ unlabelled nodes.
Community detection in censored hypergraph
In practice, a network may has censored (or missing) values and it is shown that censored values have non-negligible effect on the structural properties of a network.
Online Statistical Inference for Parameters Estimation with Linear-Equality Constraints
Stochastic gradient descent (SGD) and projected stochastic gradient descent (PSGD) are scalable algorithms to compute model parameters in unconstrained and constrained optimization problems.
Information Limits for Detecting a Subhypergraph
We consider the problem of recovering a subhypergraph based on an observed adjacency tensor corresponding to a uniform hypergraph.
Heterogeneous Dense Subhypergraph Detection
We study the problem of testing the existence of a heterogeneous dense subhypergraph.
A Practical Two-Sample Test for Weighted Random Graphs
In this paper, we study the weighted graph two-sample hypothesis testing problem and propose a practical test statistic.
Methodology Applications
A practical test for a planted community in heterogeneous networks
However, the computational complexity of the scan test is generally not polynomial in the graph size, which makes the test impractical for large or moderate networks.
Sharp detection boundaries on testing dense subhypergraph
In both scenarios, sharp detectable boundaries are characterized by the appropriate model parameters.
A likelihood-ratio type test for stochastic block models with bounded degrees
A fundamental problem in network data analysis is to test Erd\"{o}s-R\'{e}nyi model $\mathcal{G}\left(n,\frac{a+b}{2n}\right)$ versus a bisection stochastic block model $\mathcal{G}\left(n,\frac{a}{n},\frac{b}{n}\right)$, where $a, b>0$ are constants that represent the expected degrees of the graphs and $n$ denotes the number of nodes.
