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  Semi-supervised Learning on Directed Graphs

Zhou, D., Schölkopf, B., & Hofmann, T. (2005). Semi-supervised Learning on Directed Graphs. In L. Saul, Y. Weiss, & L. Bottou (Eds.), Advances in Neural Information Processing Systems 17 (pp. 1633-1640). Cambridge, MA, USA: MIT Press.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D52B-B Version Permalink: http://hdl.handle.net/21.11116/0000-0005-3253-5
Genre: Conference Paper

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 Creators:
Zhou, D1, 2, Author              
Schölkopf, B1, 2, Author              
Hofmann, T1, 2, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Given a directed graph in which some of the nodes are labeled, we investigate the question of how to exploit the link structure of the graph to infer the labels of the remaining unlabeled nodes. To that extent we propose a regularization framework for functions defined over nodes of a directed graph that forces the classification function to change slowly on densely linked subgraphs. A powerful, yet computationally simple classification algorithm is derived within the proposed framework. The experimental evaluation on real-world Web classification problems demonstrates encouraging results that validate our approach.

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 Dates: 2005-07
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 2781
 Degree: -

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Title: Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004)
Place of Event: Vancouver, BC, Canada
Start-/End Date: 2004-12-13 - 2004-12-16

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Title: Advances in Neural Information Processing Systems 17
Source Genre: Proceedings
 Creator(s):
Saul, LK, Editor
Weiss, Y, Editor
Bottou, L, Editor
Affiliations:
-
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1633 - 1640 Identifier: ISBN: 0-262-19534-8