Statistica Sinica 27 (2017), 1639-1659
Abstract: We study the problem of community recovery in stochastic block models and degree corrected block models. We show that a simple sample splitting trick can refine almost any approximately correct community recovery method to achieve exactly correct community recovery when the expected node degrees are of order log n or higher. Our results simplify and extend some of the previous work on exact community recovery using sample splitting, and provide better theoretical guarantees for degree corrected stochastic block models.
Key words and phrases: Block models, clustering, community detection, network data, sample splitting.