Conventional network data have largely focused on pairwise interactions between two
entities, yet multi-way interactions among multiple entities have been frequently observed in …

In Section A of the Supplementary Material, we provide additional theoretical results,
including upper and lower bounds when ρ is of constant order (Section A. 1), upper bounds …

Communities in multi-layer networks consist of nodes with similar connectivity patterns
across all layers. This article proposes a tensor-based community detection method in multi …

We investigate a generalized framework to estimate a latent low-rank plus sparse tensor,
where the low-rank tensor often captures the multi-way principal components and the sparse …

In this article, we study large-dimensional matrix factor models and estimate the factor
loading matrices and factor score matrix by minimizing square loss function. Interestingly …

Suppose we are given an n-dimensional order-3 symmetric tensor T∈(ℝ n)⊗ 3 that is the
sum of r random rank-1 terms. The problem of recovering the rank-1 components is possible …

Understanding dramatic changes in the evolution of networks is central to statistical network
inference, as underscored by recent challenges of predicting and distinguishing pandemic …

Inference for low-rank tensors-no need to debias Page 1 The Annals of Statistics 2022, Vol. 50,
No. 2, 1220–1245 https://doi.org/10.1214/21-AOS2146 © Institute of Mathematical Statistics …

Network method of moments (Ann. Statist. 39 (2011) 2280–2301) is an important tool for
nonparametric network inference. However, there has been little investigation on accurate …

This paper investigates the problem of exact community recovery in the symmetric $ d $-
uniform $(d\geq 2) $ hypergraph stochastic block model ($ d $-HSBM). In this model, a $ d …