The Department of Statistics and Actuarial Science Spring Colloquium Series presents:
Srijan Sengupta, Associate Professor, Department of Statistics, North Carolina State University
"Finding Anomalous Cliques in Inhomogeneous Networks using Egonets"
Abstract: Cliques, or fully connected subgraphs, are among the most important and well-studied graph motifs in network science. We consider the problem of finding a statistically anomalous clique hidden in a large network. There are two parts to this problem: (1) detection, i.e., determining whether an anomalous clique is present, and (2) localization, i.e., determining which vertices of the network constitute the detected clique. While this problem has been extensively studied under the homogeneous Erdos-Renyi model, little progress has been made beyond this simple setting, and no existing method can perform detection and localization in inhomogeneous networks within finite time. To address this gap, we first show that in homogeneous networks, the anomalousness of a clique depends solely on its size. This property does not carry over to inhomogeneous networks, where the identity of the vertices forming the clique plays a critical role, and a smaller clique can be more anomalous than a larger one. Building on this insight, we propose a unified method for clique detection and localization based on a class of subgraphs called egonets. The proposed method generalizes to a wide variety of inhomogeneous network models and is naturally amenable to parallel computing. We establish the theoretical properties of the proposed method and demonstrate its empirical performance through simulation studies and application to two real-world networks.
This virtual presentation begins at 3:15 p.m.
Topic: Statistics and Actuarial Science Weekly Seminars
Time: Feb 19, 2025 03:15 PM Central Time (US and Canada)
Meeting ID: 953 2875 9287
Passcode: 595969