A transitive aligned Weisfeiler-Lehman subtree kernel


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.

Publication DOI: https://doi.org/10.1109/ICPR.2016.7899666
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
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Event Title: 23rd International Conference on Pattern Recognition
Event Type: Other
Event Dates: 2016-12-04 - 2016-12-08
Uncontrolled Keywords: Computer Vision and Pattern Recognition
ISBN: 978-1-5090-4847-2
Last Modified: 01 Feb 2024 08:01
Date Deposited: 07 Nov 2016 08:05
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2017-04-13
Accepted Date: 2016-07-13
Authors: Bai, Lu
Rossi, Luca (ORCID Profile 0000-0002-6116-9761)
Cui, Lixin
Hancock, Edwin R.



Version: Accepted Version

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