Partial Recovery of Erdős-Rényi Graph Alignment via $k$-Core Alignment

September 10, 2018 · Declared Dead · 🏛 Proceedings of the ACM on Measurement and Analysis of Computing Systems

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Authors Daniel Cullina, Negar Kiyavash, Prateek Mittal, H. Vincent Poor arXiv ID 1809.03553 Category cs.IT: Information Theory Cross-listed cs.LG Citations 57 Venue Proceedings of the ACM on Measurement and Analysis of Computing Systems Last Checked 5 months ago
Abstract
We determine information theoretic conditions under which it is possible to partially recover the alignment used to generate a pair of sparse, correlated Erdős-Rényi 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.
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