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New graph matching algorithm achieves near-exact recovery in near-quadratic time

By PulseAugur Editorial · [3 sources] ·

Researchers have developed a new graph matching algorithm that operates in nearly quadratic time, achieving almost exact recovery under specific conditions. This algorithm utilizes local tree correlation tests and a rank-based approach, bypassing the need for computationally intensive threshold calculations. The work establishes a new analysis for tree correlation tests in diverging-degree regimes and demonstrates a threshold for graph matching, ultimately coupling rank-based and threshold-based methods for improved recovery. AI

IMPACT This research contributes to foundational graph theory and algorithms, potentially impacting AI applications that rely on graph analysis and matching.

RANK_REASON Academic paper detailing a new algorithm and theoretical results.

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

New graph matching algorithm achieves near-exact recovery in near-quadratic time

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COVERAGE [3]

  1. arXiv stat.ML TIER_1 English(EN) · Jiale Cheng, Ziao Wang, Lei Ying ·

    Achieving Almost Exact Recovery in Almost Quadratic Time: Rank-Based Graph Matching via Local Tree Correlation Tests

    arXiv:2607.09087v1 Announce Type: cross Abstract: This paper studies graph matching under the correlated $\text{Erd\H{o}s-R\'{e}nyi}$ (ER) graph pair model. This model first samples an $\mathrm{ER}(n,\frac{\lambda}{ns})$ base graph, whose edges are then independently subsampled t…

  2. arXiv stat.ML TIER_1 English(EN) · Lei Ying ·

    Achieving Almost Exact Recovery in Almost Quadratic Time: Rank-Based Graph Matching via Local Tree Correlation Tests

    This paper studies graph matching under the correlated $\text{Erdős-Rényi}$ (ER) graph pair model. This model first samples an $\mathrm{ER}(n,\fracλ{ns})$ base graph, whose edges are then independently subsampled twice with probability $s$ to produce two correlated $\mathrm{ER}(n…

  3. arXiv stat.ML TIER_1 English(EN) · Lei Ying ·

    Achieving Almost Exact Recovery in Almost Quadratic Time: Rank-Based Graph Matching via Local Tree Correlation Tests

    This paper studies graph matching under the correlated $\text{Erdős-Rényi}$ (ER) graph pair model. This model first samples an $\mathrm{ER}(n,\fracλ{ns})$ base graph, whose edges are then independently subsampled twice with probability $s$ to produce two correlated $\mathrm{ER}(n…

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