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  Learning with Hypergraphs: Clustering, Classification, and Embedding

Zhou, D., Huang, J., & Schölkopf, B. (2007). Learning with Hypergraphs: Clustering, Classification, and Embedding. Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference, 1601-1608.

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Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-CBED-8 Versions-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-CBEE-6
Genre: Konferenzbeitrag

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 Urheber:
Zhou, D1, Autor           
Huang, J1, Autor           
Schölkopf, B1, Autor           
Schölkopf, Herausgeber
B., Herausgeber
Platt, J., Herausgeber
Hofmann, T., Herausgeber
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Zusammenfassung: We usually endow the investigated objects with pairwise relationships, which can be illustrated as graphs. In many real-world problems, however, relationships among the objects of our interest are more complex than pairwise. Naively squeezing the complex relationships into pairwise ones will inevitably lead to loss of information which can be expected valuable for our learning tasks however. Therefore we consider using hypergraphs instead to completely represent complex relationships among the objects of our interest, and thus the problem of learning with hypergraphs arises. Our main contribution in this paper is to generalize the powerful methodology of spectral clustering which originally operates on undirected graphs to hypergraphs, and further develop algorithms for hypergraph embedding and transductive classi¯cation on the basis of the spectral hypergraph clustering approach. Our experiments on a number of benchmarks showed the advantages of hypergraphs over usual graphs.

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Sprache(n):
 Datum: 2007-09
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: ISBN: 0-262-19568-2
URI: http://nips.cc/Conferences/2006/
BibTex Citekey: 4164
 Art des Abschluß: -

Veranstaltung

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Titel: Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006)
Veranstaltungsort: Vancouver, BC, Canada
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Titel: Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Cambridge, MA, USA : MIT Press
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 1601 - 1608 Identifikator: -