The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
|
Activity Number:
|
578
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Section on Bayesian Statistical Science
|
| Abstract - #306338 |
|
Title:
|
A Bayesian Degree-Corrected Stochastic Block Model for Community Detection
|
|
Author(s):
|
Luis Carvalho*+ and Lijun Peng
|
|
Companies:
|
Boston University and Boston University
|
|
Address:
|
111 Cummington St, Boston, MA, 02215, United States
|
|
Keywords:
|
network modeling ;
centroid estimation ;
modularity
|
|
Abstract:
|
We discuss a degree-corrected version of a stochastic block model that aims to achieve a better resolution for community identification. We follow a fully Bayesian approach and conduct inference based on a principled centroid estimator of community labels. To this end, an efficient Gibbs sampler is developed. We demonstrate the proposed model and inference on a number of classical network datasets. Finally, we offer a few concluding remarks on the model implementation and directions for future work.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.