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  The skew spectrum of graphs

Kondor, R., & Borgwardt, K. (2008). The skew spectrum of graphs. In Twenty-Fifth International Conference on Machine Learning (ICML 2008) (pp. 496-503). New York, NY, USA: ACM Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C847-3 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C848-1
Genre: Conference Paper

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 Creators:
Kondor, R, Author
Borgwardt, K1, Author           
Cohen, Editor
W.W., Editor
McCallum, A., Editor
Roweis, S.T., Editor
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: The central issue in representing graph-structured data instances in learning algorithms is designing features which are invariant to permuting the numbering of the vertices. We present a new system of invariant graph features which we call the skew spectrum of graphs. The skew spectrum is based on mapping the adjacency matrix of any (weigted, directed, unlabeled) graph to a function on the symmetric group and computing bispectral invariants. The reduced form of the skew spectrum is computable in O(n3) time, and experiments show that on several benchmark datasets it can outperform state of the art graph kernels.

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 Dates: 2008-07
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISBN: 978-1-605-58205-4
URI: http://dl.acm.org/citation.cfm?id=1390219
DOI: 10.1145/1390156.1390219
BibTex Citekey: KondorB2008
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Title: Twenty-Fifth International Conference on Machine Learning (ICML 2008)
Place of Event: Helsinki, Finland
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Title: Twenty-Fifth International Conference on Machine Learning (ICML 2008)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: New York, NY, USA : ACM Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 496 - 503 Identifier: -