research
∙
08/04/2023
Distributional Theory and Statistical Inference for Linear Functions of Eigenvectors with Small Eigengaps
Spectral methods have myriad applications in high-dimensional statistics...
share
research
∙
05/10/2023
An Overview of Asymptotic Normality in Stochastic Blockmodels: Cluster Analysis and Inference
This paper provides a selective review of the statistical network analys...
research
∙
05/04/2023
Semisupervised regression in latent structure networks on unknown manifolds
Random graphs are increasingly becoming objects of interest for modeling...
research
∙
12/16/2022
Estimating Higher-Order Mixed Memberships via the ℓ_2,∞ Tensor Perturbation Bound
Higher-order multiway data is ubiquitous in machine learning and statist...
research
∙
02/08/2022
Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms
Sparse Principal Component Analysis (PCA) is a prevalent tool across a p...
research
∙
05/27/2021
Entrywise Estimation of Singular Vectors of Low-Rank Matrices with Heteroskedasticity and Dependence
We propose an estimator for the singular vectors of high-dimensional low...
research
∙
12/17/2020
Nonparametric Two-Sample Hypothesis Testing for Random Graphs with Negative and Repeated Eigenvalues
We propose a nonparametric two-sample test statistic for low-rank, condi...
research
∙
08/21/2020
Correcting a Nonparametric Two-sample Graph Hypothesis Test for Graphs with Different Numbers of Vertices
Random graphs are statistical models that have many applications, rangin...
research
∙
03/31/2020
On Two Distinct Sources of Nonidentifiability in Latent Position Random Graph Models
Two separate and distinct sources of nonidentifiability arise naturally ...
research
∙
05/06/2019