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  Fast subtree kernels on graphs

Shervashidze, N., & Borgwardt, K. (2010). Fast subtree kernels on graphs. Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009, 1660-1668.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-C0C6-B Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-C0C7-9
Genre: Conference Paper

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 Creators:
Shervashidze, N1, Author              
Borgwardt, KM1, Author              
Bengio, Editor
Y., Editor
Schuurmans, D., Editor
Lafferty, J., Editor
Williams, C., Editor
Culotta, A., Editor
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, escidoc:1497794              

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 Abstract: In this article, we propose fast subtree kernels on graphs. On graphs with n nodes and m edges and maximum degree d, these kernels comparing subtrees of height h can be computed in O(mh), whereas the classic subtree kernel by Ramon Gärtner scales as O(n24dh). Key to this efficiency is the observation that the Weisfeiler-Lehman test of isomorphism from graph theory elegantly computes a subtree kernel as a byproduct. Our fast subtree kernels can deal with labeled graphs, scale up easily to large graphs and outperform state-of-the-art graph kernels on several classification benchmark datasets in terms of accuracy and runtime.

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Language(s):
 Dates: 2010-04
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: ISBN: 978-1-615-67911-9
URI: http://books.nips.cc/nips22.html
BibTex Citekey: 6080
 Degree: -

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Title: 23rd Annual Conference on Neural Information Processing Systems (NIPS 2009)
Place of Event: Vancouver, BC, Canada
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Title: Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Red Hook, NY, USA : Curran
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1660 - 1668 Identifier: -