Network data: Modeling and Statistical Analysis

Job Candidate Talk
Thursday, January 10, 2019 - 11:00am for 1 hour (actually 50 minutes)
Skiles 006
Subhabrata Sen – MIT – ssen90@mit.edu
Michael Damron
Network data arises frequently in modern scientific applications. These networks often have specific characteristics such as edge sparsity, heavy-tailed degree distribution etc. Some broad challenges arising in the analysis of such datasets include (i) developing flexible, interpretable models for network datasets, (ii) testing for goodness of fit, (iii) provably recovering latent structure from such data.In this talk, we will discuss recent progress in addressing very specific instantiations of these challenges. In particular, we will1. Interpret the Caron-Fox model using notions of graph sub-sampling, 2. Study model misspecification due to rare, highly “influential” nodes, 3. Discuss recovery of community structure, given additional covariates.