An Extended Path Following Algorithm for Graph-Matching Problem

IEEE Transactions on Pattern Analysis and Machine Intelligence
Zhi-Yong LiuLei Xu

Abstract

The path following algorithm was proposed recently to approximately solve the matching problems on undirected graph models and exhibited a state-of-the-art performance on matching accuracy. In this paper, we extend the path following algorithm to the matching problems on directed graph models by proposing a concave relaxation for the problem. Based on the concave and convex relaxations, a series of objective functions are constructed, and the Frank-Wolfe algorithm is then utilized to minimize them. Several experiments on synthetic and real data witness the validity of the extended path following algorithm.

References

Aug 30, 2008·Proceedings of the National Academy of Sciences of the United States of America·Rohit SinghBonnie Berger
Oct 17, 2009·IEEE Transactions on Pattern Analysis and Machine Intelligence·Mikhail ZaslavskiyJean-Philippe Vert
May 1, 1986·IEEE Transactions on Pattern Analysis and Machine Intelligence·M A Eshera, K S Fu

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Citations

Jun 1, 2014·IEEE Transactions on Pattern Analysis and Machine Intelligence· Zhi-Yong Liu, Hong Qiao
Apr 18, 2015·PloS One·Joshua T VogelsteinCarey E Priebe
Nov 26, 2015·IEEE Transactions on Pattern Analysis and Machine Intelligence·Feng Zhou, Fernando de la Torre
Jun 3, 2016·IEEE Transactions on Pattern Analysis and Machine Intelligence·Quynh NguyenMatthias Hein
Jul 12, 2017·IEEE Transactions on Neural Networks and Learning Systems·Xu YangZhi-Yong Liu

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