PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

The skew spectrum of graphs
Risi Kondor and Karsten Borgwardt
In: ICML 2008, 5-7 Jul 2008, Helisinki, Finland.

Abstract

The central issue in representing graphstructured 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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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:5314
Deposited By:Risi Kondor
Deposited On:24 March 2009