Characterising Structural Variations in Graphs

Edwin Hancock

 

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Presenter: Edwin Hancock
Type: Invited presentation
Venue: TextGraphs-5 Workshop at ACL 2010 in Uppsala
Date: July 16, 2010
Recording: Chris Biemann
Duration: 72 minutes

 

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Abstract

The talk commences by discussing some of the problems that arise when machine learning is applied to graph structures. A taxonomy of different methods organised around a) clustering b) characterisation and c) constructing generative models in the graph domain is introduced. With this taxonomy in hand, Dr. Hancock then describes a number of graph-spectral algorithms that can be applied to solve the many different problems inherent to graphs, drawing examples from computer vision research.


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Workshop Proceedings