English

A polynomial-time iterative algorithm for random graph matching with non-vanishing correlation

Data Structures and Algorithms 2024-03-07 v2 Probability Statistics Theory Machine Learning Statistics Theory

Abstract

We propose an efficient algorithm for matching two correlated Erd\H{o}s--R\'enyi graphs with nn vertices whose edges are correlated through a latent vertex correspondence. When the edge density q=nα+o(1)q= n^{- \alpha+o(1)} for a constant α[0,1)\alpha \in [0,1), we show that our algorithm has polynomial running time and succeeds to recover the latent matching as long as the edge correlation is non-vanishing. This is closely related to our previous work on a polynomial-time algorithm that matches two Gaussian Wigner matrices with non-vanishing correlation, and provides the first polynomial-time random graph matching algorithm (regardless of the regime of qq) when the edge correlation is below the square root of the Otter's constant (which is 0.338\approx 0.338).

Keywords

Cite

@article{arxiv.2306.00266,
  title  = {A polynomial-time iterative algorithm for random graph matching with non-vanishing correlation},
  author = {Jian Ding and Zhangsong Li},
  journal= {arXiv preprint arXiv:2306.00266},
  year   = {2024}
}

Comments

62 pages, 1 figure

R2 v1 2026-06-28T10:52:45.058Z