This paper gives a review of concentration inequalities which are widely employed in non-
asymptotical analyses of mathematical statistics in a wide range of settings, from distribution …

The $\beta $-model is a powerful tool for modeling network generation driven by degree
heterogeneity. Its simple yet expressive nature particularly well-suits large and sparse …

For high-dimensional models with a focus on classification performance, the ℓ 1-penalized
logistic regression is becoming important and popular. However, the Lasso estimates could …

An important question in statistical network analysis is how to estimate models of discrete
and dependent network data with intractable likelihood functions, without sacrificing …

Affiliation network is one kind of two-mode social network with two different sets of nodes
(namely, a set of actors and a set of social events) and edges representing the affiliation of …

As network data has become increasingly prevalent, a substantial amount of attention has
been paid to the privacy issue in publishing network data. One of the critical challenges for …

Edge differentially private estimation in the beta-model via jittering and method of moments
Page 1 The Annals of Statistics 2024, Vol. 52, No. 2, 708–728 https://doi.org/10.1214/24-AOS2365 …

This paper investigates the sparse β model with 𝓁 1 penalty in the field of network data
models, which is a hot topic in both statistical and social network research. We present a …

The Bradley-Terry model is a common model for analyzing paired comparison data. Under
differential private mechanism, there is a lack of asymptotic properties for the parameter …

In the case of differential privacy under the Laplace mechanism, the asymptotic properties of
parameter estimator have been derived in some special models such as β− model, but …