Contiguity and non-reconstruction results for planted partition models: the dense case
Debapratim Banerjee

TL;DR
This paper extends the understanding of the stochastic block model in dense graphs, showing contiguity and non-reconstruction results when connection probabilities grow with the number of nodes, confirming parts of a conjecture for dense cases.
Contribution
It generalizes previous results to cases where connection probabilities increase with network size, providing new thresholds for contiguity and non-reconstruction in dense stochastic block models.
Findings
Models are mutually contiguous if -b)^2< 2(1-p)(a+b)
Models are asymptotically singular if -b)^2> 2(1-p)(a+b)
Impossible to recover true labels when -b)^2< 2(1-p)(a+b)
Abstract
We consider the two block stochastic block model on nodes with asymptotically equal cluster sizes. The connection probabilities within and between cluster are denoted by and respectively. Mossel et al.(2012) considered the case when and are fixed. They proved the probability models of the stochastic block model and that of Erd{\"o}s-R{\'e}nyi graph with same average degree are mutually contiguous whenever and are asymptotically singular whenever . Mossel et al.(2012) also proved that when no algorithm is able to find an estimate of the labeling of the nodes which is positively correlated with the true labeling. It is natural to ask what happens when and both grow to infinity. We prove that their results extend to the case when and . We also…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
