Settling the Sharp Reconstruction Thresholds of Random Graph Matching

Settling the Sharp Reconstruction Thresholds of Random Graph Matching

This paper studies the problem of recovering the hidden vertex correspondence between two edge-correlated random graphs. We focus on the Gaussian model where the two graphs are complete graphs with correlated Gaussian weights and the Erdős-Rényi model where the two graphs are s...

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Bibliographic Details
Main Authors: Wu, Y. (Author), Xu, J. (Author), Yu, S.H (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
Computation theory
Correlation
Cycle decomposition of permutation
cycle decomposition of permutations
Cycle decompositions
Entropy
Erdő
Erdős-Rényi random graphs
Gaussian distribution
Gaussian model
Gaussian modeling
Graph matching
Graph matchings
Graph theory
Graphic methods
Limiting
Maximum likelihood estimation
Maximum-likelihood estimation
mutual information
Mutual information
Mutual informations
Nyi random graph
Pattern matching
Random graphs
Random variables
Recovery
recovery threshold
Recovery thresholds
S-Ré
Standards
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