Bai, Lu, Rossi, Luca and Hancock, Edwin R orcid.org/0000-0003-4496-2028 (2015) An Aligned Subtree Kernel for Weighted Graphs. In: International Conference on Machine Learning (ICML) 2015. , pp. 30-39.
Abstract
In this paper, we develop a new entropic match- ing kernel for weighted graphs by aligning depth- based representations. We demonstrate that this kernel can be seen as an aligned subtree kernel that incorporates explicit subtree correspondences, and thus addresses the drawback of neglecting the relative locations between substructures that arises in the R-convolution kernels. Experiments on standard datasets demonstrate that our kernel can easily outperform state-of-the-art graph kernels in terms of classification accuracy.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 06 Jul 2016 09:02 |
Last Modified: | 21 Jan 2025 18:22 |
Status: | Published |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:88204 |