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Volumn , Issue , 2015, Pages 225-230

Exact ICL maximization in a non-stationary time extension of the latent block model for dynamic networks

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS; NEURAL NETWORKS;

EID: 84961839143     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (6)

References (7)
  • 1
    • 84901504986 scopus 로고    scopus 로고
    • Clustering the vélib - Dynamic origin/destination ows using a family of poisson mixture models
    • A.N. Randriamanamihaga, E. Côme, L. Oukhellou and G. Govaert, Clustering the Vélib - dynamic Origin/Destination ows using a family of Poisson mixture models, Neurocom- puting, vol. 141, pp. 124-138, 2014.
    • (2014) Neurocomputing , vol.141 , pp. 124-138
    • Randriamanamihaga, A.N.1    Côme, E.2    Oukhellou, L.3    Govaert, G.4
  • 5
    • 0034228914 scopus 로고    scopus 로고
    • Assessing a mixture model for clustering with the integrated completed likelihood
    • C. Biernacky, G. Celeux and G. Govaert, Assessing a mixture model for clustering with the integrated completed likelihood, IEEE Trans. Pattern Anal. Machine Intel, vol.7, pp. 719-725, 2000.
    • (2000) IEEE Trans. Pattern Anal. Machine Intel , vol.7 , pp. 719-725
    • Biernacky, C.1    Celeux, G.2    Govaert, G.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.