Robust Label Propagation on Multiple Networks | IEEE Journals & Magazine | IEEE Xplore
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Robust Label Propagation on Multiple Networks


Abstract:

Transductive inference on graphs such as label propagation algorithms is receiving a lot of attention. In this paper, we address a label propagation problem on multiple n...Show More

Abstract:

Transductive inference on graphs such as label propagation algorithms is receiving a lot of attention. In this paper, we address a label propagation problem on multiple networks and present a new algorithm that automatically integrates structure information brought in by multiple networks. The proposed method is robust in that irrelevant networks are automatically deemphasized, which is an advantage over Tsuda's approach (2005). We also show that the proposed algorithm can be interpreted as an expectation-maximization (EM) algorithm with a student-t prior. Finally, we demonstrate the usefulness of our method in protein function prediction and digit classification, and show analytically and experimentally that our algorithm is much more efficient than existing algorithms.
Published in: IEEE Transactions on Neural Networks ( Volume: 20, Issue: 1, January 2009)
Page(s): 35 - 44
Date of Publication: 12 December 2008

ISSN Information:

PubMed ID: 19095533

References

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