Partial Recovery of ErdH{o}s-R\'enyi Graph Alignment via k-Core Alignment
read the original abstract
We determine information theoretic conditions under which it is possible to partially recover the alignment used to generate a pair of sparse, correlated Erd\H{o}s-R\'enyi graphs. To prove our achievability result, we introduce the $k$-core alignment estimator. This estimator searches for an alignment in which the intersection of the correlated graphs using this alignment has a minimum degree of $k$. We prove a matching converse bound. As the number of vertices grows, recovery of the alignment for a fraction of the vertices tending to one is possible when the average degree of the intersection of the graph pair tends to infinity. It was previously known that exact alignment is possible when this average degree grows faster than the logarithm of the number of vertices.
This paper has not been read by Pith yet.
Forward citations
Cited by 1 Pith paper
-
Spectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model
GRAMPA recovers exact vertex correspondence in the Gaussian Wigner model with high probability for σ = O(1/log n) via a regularized quadratic relaxation using all eigenvector pairs.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.