种子图匹配:高效算法和理论保证

Farhad Shirani, S. Garg, E. Erkip
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引用次数: 48

摘要

本文提出了一种新的图匹配信息理论框架。在此框架下,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,并利用类型分析导出了图同构匹配成功的充分条件。在此基础上,提出了一种时间复杂度为多项式的种子匹配算法。该算法使用“典型匹配”和点对点通信技术进行可靠匹配。假设在关联图对上建立Erdös-Renyi模型,表明当种子数量与图中顶点数量成对数增长时,保证匹配成功。对数系数显示为与两个图中边缘变量之间的互信息成反比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Seeded graph matching: Efficient algorithms and theoretical guarantees
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.
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