arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2310.14701math.COmath.SP
收藏

闪电图匹配

Lightning graph matching

Binrui. shen, Qiang. niu, Shengxin. zhu

AI总结:

本文提出LiSA算法,将图匹配问题转化为1D线性分配问题,通过向量排序高效求解,将复杂度降至$\mathcal{O}(n^2)$,适用于大规模任务。

摘要:

图匹配旨在寻找两个图之间的对应关系,是模式识别中的一项基础任务。经典谱匹配算法的时间复杂度为$\mathcal{O}(n^4)$,空间复杂度为$\mathcal{O}(n^4)$,其中$n$为节点数。这种复杂度限制了其在大规模图匹配任务中的适用性。本文提出对谱匹配的高效重新设计,将图匹配问题转化为1D线性分配问题,通过对两个$n \times 1$向量排序即可高效求解。所得算法名为lightning spectral assignment method (LiSA),其复杂度为$\mathcal{O}(n^2)$。数值实验验证了该策略的效率及理论分析。

英文摘要:

Graph matching aims to find correspondences between two graphs. It is a fundamental task in pattern recognition. The classical spectral matching algorithm has time complexity $\mathcal{O}(n^4)$ and space complexity $\mathcal{O}(n^4)$, where $n$ is the number of nodes. Such a complexity limits the applicability to large-scale graph matching tasks. This paper proposes an efficient redesign of spectral matching by transforming the graph matching problem into a 1D linear assignment problem, which can be solved efficiently by sorting two $n \times 1$ vectors. The resulting algorithm is named the lightning spectral assignment method (LiSA), which enjoys a complexity of $\mathcal{O}(n^2)$. Numerical experiments demonstrate the efficiency and the theoretical analysis of the strategy.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑