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Consistent polynomial-time unseeded graph matching for Lipschitz graphons
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We propose a consistent polynomial-time method for the unseeded node matching problem for networks with smooth underlying structures. Despite widely conjectured by the research community that the structured graph matching problem to be significantly easier than its worst case counterpart, well-known to be NP-hard, the statistical version of the problem has stood a challenge that resisted any solution both provable and polynomial-time. The closest existing work requires quasi-polynomial time. Our method is based on the latest advances in graphon estimation techniques and analysis on the concentration of empirical Wasserstein distances. Its core is a simple yet unconventional sampling-and-matching scheme that reduces the problem from unseeded to seeded. Our method allows flexible efficiencies, is convenient to analyze and potentially can be extended to more general settings. Our work enables a rich variety of subsequent estimations and inferences.
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Asymptotically perfect seeded graph matching without edge correlation (and applications to inference)
OmniMatch provably and asymptotically perfectly aligns unseeded vertices across independent random dot product graphs using only a seed set and shared latent structure, with no edge correlation.
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