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Volumn 1, Issue , 2008, Pages 432-442

Graph mining with variational dirichlet process mixture models

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; DATA HANDLING; FREE ENERGY;

EID: 52649090208     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972788.39     Document Type: Conference Paper
Times cited : (12)

References (17)
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    • C. Helma, T. Cramer, S. Kramer, and L.D. Raedt. Data mining and machine learning techniques for the identification of mutagenicity inducing substructures and structure activity relationships of noncongeneric compounds. J. Chem. Inf. Comput. Sci., 44:1402-1411, 2004.
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  • 6
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    • J. Kazius, S. Nijssen, J. Kok, and T. Back A.P. Ijzerman. Substructure mining using elaborate chemical representation. J. Chem. Inf. Model, 46:597-605, 2006.
    • J. Kazius, S. Nijssen, J. Kok, and T. Back A.P. Ijzerman. Substructure mining using elaborate chemical representation. J. Chem. Inf. Model, 46:597-605, 2006.
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    • Variable selection in clustering via Dirichlet mixture models
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    • A constructive definition of Dirichlet priors
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    • (1994) Statistica Sinica , vol.4 , pp. 639-650
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    • 4544354704 scopus 로고    scopus 로고
    • Variational Bayesian feature selection for Gaussian mixture models
    • F. Valente and C. Wellekens. Variational Bayesian feature selection for Gaussian mixture models. In ICASSP'04, volume 1, pages 513-516, 2004.
    • (2004) ICASSP'04 , vol.1 , pp. 513-516
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