136 citations · 408 across the 33 of their papers we have counts for
9 papers · 1 filter
Consistent Identification of Top- Nodes in Noisy Networks
Hui Shen, Eric D. Kolaczyk
Identifying the most influential nodes in a network, typically using centrality measures, is a central task in applied network analysis. However, real-world networks are often cons…
Autoregressive networks with dependent edges
Jinyuan Chang, Qin Fang, Eric D. Kolaczyk +2
We propose an autoregressive framework for modelling dynamic networks with dependent edges. It encompasses models that accommodate, for example, transitivity, degree heterogenenity…
Edge differentially private estimation in the -model via jittering and method of moments
Jinyuan Chang, Qiao Hu, Eric D. Kolaczyk +2
A standing challenge in data privacy is the trade-off between the level of privacy and the efficiency of statistical inference. Here we conduct an in-depth study of this trade-off…
Averages of Unlabeled Networks: Geometric Characterization and Asymptotic Behavior
Eric Kolaczyk, Lizhen Lin, Steven Rosenberg +2
It is becoming increasingly common to see large collections of network data objects -- that is, data sets in which a network is viewed as a fundamental unit of observation. As a re…
On the Propagation of Low-Rate Measurement Error to Subgraph Counts in Large Networks
Prakash Balachandran, Eric D. Kolaczyk, Weston Viles
Our work in this paper is inspired by a statistical observation that is both elementary and broadly relevant to network analysis in practice -- that the uncertainty in approximatin…
Weighted Frechet Means as Convex Combinations in Metric Spaces: Properties and Generalized Median Inequalities
Cedric E. Ginestet, Andrew Simmons, Eric D. Kolaczyk
In this short note, we study the properties of the weighted Frechet mean as a convex combination operator on an arbitrary metric space, (Y,d). We show that this binary operator is…