Comparative study for inference of hidden classes in stochastic block models

Pan Zhang, Florent Krzakala, Jörg Reichardt, Lenka Zdeborová
2012 Journal of Statistical Mechanics: Theory and Experiment  
Inference of hidden classes in stochastic block model is a classical problem with important applications. Most commonly used methods for this problem involve naïve mean field approaches or heuristic spectral methods. Recently, belief propagation was proposed for this problem. In this contribution we perform a comparative study between the three methods on synthetically created networks. We show that belief propagation shows much better performance when compared to naïve mean field and spectral
more » ... pproaches. This applies to accuracy, computational efficiency and the tendency to overfit the data.
doi:10.1088/1742-5468/2012/12/p12021 fatcat:7uvcz7mrybgxlblz45fwbqvffa