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Seeded graph matching: Efficient algorithms and theoretical guarantees

机译:种子图匹配:高效的算法和理论保证

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In this paper, a new information theoretic framework for graph matching is introduced. Using this framework, the graph isomorphism and seeded graph matching problems are studied. The maximum degree algorithm for graph isomorphism is analyzed and sufficient conditions for successful matching are rederived using type analysis. Furthermore, a new seeded matching algorithm with polynomial time complexity is introduced. The algorithm uses `typicality matching' and techniques from point-to-point communications for reliable matching. Assuming an Erdös-Renyi model on the correlated graph pair, it is shown that successful matching is guaranteed when the number of seeds grows logarithmically with the number of vertices in the graphs. The logarithmic coefficient is shown to be inversely proportional to the mutual information between the edge variables in the two graphs.
机译:本文介绍了一种新的图匹配信息理论框架。使用该框架,研究了图同构和种子图匹配问题。分析了图同构的最大度算法,并使用类型分析重新获得了成功匹配的充分条件。此外,引入了一种新的具有多项式时间复杂度的种子匹配算法。该算法使用“典型匹配”和点对点通信中的技术来实现可靠的匹配。假设在相关图对上有一个Erdös-Renyi模型,表明当种子数与图中顶点数成对数增长时,可以确保成功匹配。对数系数显示为与两个图中的边缘变量之间的互信息成反比。

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