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  A kernel method for unsupervised structured network inference

Lippert, C., Stegle, O., Ghahramani, Z., & Borgwardt, K. (2009). A kernel method for unsupervised structured network inference. In D. Van Dyk, & M. Welling (Eds.), Twelfth International Conference on Artificial Intelligence and Statistics (AIStats 2009) (pp. 368-375). Cambridge, MA, USA: MIT Press.

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 Creators:
Lippert, C1, 2, Author           
Stegle, O, Author           
Ghahramani, Z, Author
Borgwardt, KM1, 2, Author           
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Former Research Group Machine Learning and Computational Biology, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528696              

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 Abstract: Network inference is the problem of inferring edges between a set of real-world objects, for instance, interactions between pairs of proteins in bioinformatics. Current kernel-based approaches to this problem share a set of common features: (i) they are supervised and hence require labeled training data; (ii) edges in the network are treated as mutually independent and hence topological properties are largely ignored; (iii) they lack a statistical interpretation. We argue that these common assumptions are often undesirable for network inference, and propose (i) an unsupervised kernel method (ii) that takes the global structure of the network into account and (iii) is statistically motivated. We show that our approach can explain commonly used heuristics in statistical terms. In experiments on social networks, different variants of our method demonstrate appealing predictive performance.

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 Dates: 2009-04
 Publication Status: Published in print
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 Identifiers: BibTex Citekey: 5663
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Title: Twelfth International Conference on Artificial Intelligence and Statistics (AIStats 2009)
Place of Event: Clearwater Beach, FL, USA
Start-/End Date: 2009-04-16 - 2009-04-18

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Title: Twelfth International Conference on Artificial Intelligence and Statistics (AIStats 2009)
Source Genre: Proceedings
 Creator(s):
Van Dyk, D, Editor
Welling, M, Editor
Affiliations:
-
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 368 - 375 Identifier: -

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Title: JMLR Workshop and Conference Proceedings
Source Genre: Series
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Pages: - Volume / Issue: 5 Sequence Number: - Start / End Page: - Identifier: -