6 citations · 6 across the 6 of their papers we have counts for
7 papers · 1 filter
Spectral clustering of network time series via the sample covariance matrix
Brendan Martin, Joshua Agterberg, Mihai Cucuringu +2
Spectral clustering for community detection is analysed in multivariate time series models whose dependence structure is determined by an unobserved stochastic blockmodel. We estab…
Statistically and Computationally Optimal Estimation and Inference of Common Subspaces
Joshua Agterberg
Given multiple data matrices, many problems in statistics and data science rely on estimating a common subspace that captures certain structure shared by all the data matrices. In…
Statistical Inference for Linear Functions of Eigenvectors with Small Eigengaps
Joshua Agterberg
Spectral methods have myriad applications in high-dimensional statistics and data science, and while previous works have primarily focused on or eigenvec…
Nonparametric two-sample hypothesis testing for low-rank random graphs of differing sizes
Joshua Agterberg, Minh Tang, Carey Priebe
Given two networks of differing sizes, it is of interest to test whether the two networks belong to the same distribution. We formalize the notion of "equality of distribution" und…
Joint Spectral Clustering in Multilayer Degree-Corrected Stochastic Blockmodels
Joshua Agterberg, Zachary Lubberts, Jesús Arroyo
Modern network datasets are often composed of multiple layers, either as different views, time-varying observations, or independent sample units, resulting in collections of networ…
An Overview of Asymptotic Normality in Stochastic Blockmodels: Cluster Analysis and Inference
Joshua Agterberg, Joshua Cape
This paper provides a selective review of the statistical network analysis literature focused on clustering and inference problems for stochastic blockmodels and their variants. We…