Efficient Belief Propagation for Graph Matching

Efficient Belief Propagation for Graph Matching
复制标题

DOI:
10.1109/icassp40776.2020.9053147
复制
发表时间:
2020-05
期刊:
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
影响因子:
--
通讯作者:
Efe Onaran;Soledad Villar
Efe Onaran;Soledad Villar
中科院分区:
其他
文献类型:
--
作者:
Efe Onaran;Soledad Villar

文献摘要

相似文献

在这篇短文中,我们推导了一种新的图匹配的信任传播算法,并在匹配随机图的情况下对其进行了数值评估。与文献中的主要可用算法相比,该算法具有更低的渐近时间复杂度,而不会显著影响精度。本文的扩展版本正在准备中,其中包含进一步的理论和数值模拟。
In this short note we derive a novel belief propagation algorithm for graph matching and we numerically evaluate it in the context of matching random graphs. The derived algorithm has a lower asymptotic time-complexity without significantly compromising the accuracy compared to leading available algorithms in the literature. An extended version of this article, with further theory and numerical simulations is in preparation.