A transitive aligned Weisfeiler-Lehman subtree kernel

Lu Bai, Luca Rossi, Lixin Cui, Edwin R. Hancock

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


In this paper, we develop a new transitive aligned Weisfeiler-Lehman subtree kernel. This kernel not only overcomes the shortcoming of ignoring correspondence information between isomorphic substructures that arises in existing R-convolution kernels, but also guarantees the transitivity between the correspondence information that is not available for existing matching kernels. Our kernel outperforms state-of-the-art graph kernels in terms of classification accuracy on standard graph datasets.

Original languageEnglish
Title of host publication2016 23rd International Conference on Pattern Recognition, ICPR 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781509048472
Publication statusPublished - 1 Jan 2016
Externally publishedYes
Event23rd International Conference on Pattern Recognition, ICPR 2016 - Cancun Center, Cancun, Mexico
Duration: 4 Dec 20168 Dec 2016

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651


Conference23rd International Conference on Pattern Recognition, ICPR 2016

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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