Learning Mixed Membership Community Models: A statistical and a Computational Framework

Abstract

The objective of this research is to study and develop a hierarchical Bayesian framework that can incorporate mixed memberships or multiple communities for each node in the network. At the same time, we will also develop tractable computational methods that can be guaranteed to correctly discover the hidden communities in the network.

Document Details

Document Type
DoD Grant Award
Publication Date
Mar 23, 2016
Source ID
FA95501510221

Entities

People

  • Anima Anandkumar

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of California, Irvine

Tags

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Computer Networking
  • Defense Technology Research and Development.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks