A transitive aligned Weisfeiler-Lehman subtree kernel

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

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication


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
Number of pages6
ISBN (Electronic)978-1-5090-4847-2
Publication statusPublished - 13 Apr 2017
Event23rd International Conference on Pattern Recognition: ICPR 2016 - Cancun, Mexico
Duration: 4 Dec 20168 Dec 2016


Conference23rd International Conference on Pattern Recognition

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