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Volumn , Issue PART 1, 2013, Pages 249-257

Learning linear Bayesian networks with latent variables

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS;

EID: 84897557825     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (87)

References (33)
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    • Blei, D.M.1    Ng, A.Y.2    Jordan, M.I.3
  • 10
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    • Reconstruction of Markov random fields from samples: Some observations and algorithms
    • Bresler, G., Mossel, E., and Sly, A. Reconstruction of Markov random fields from samples: some observations and algorithms. In APPROX, 2008.
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    • Bresler, G.1    Mossel, E.2    Sly, A.3
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    • Latent variable graphical model selection via convex optimization
    • to appear
    • Chandrasekaran, V., Parrilo, P. A., and Willsky, A. S. Latent variable graphical model selection via convex optimization. Annals of Statistics (to appear), 2012.
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    • Chandrasekaran, V.1    Parrilo, P.A.2    Willsky, A.S.3
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    • Chickering, D.M.1
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    • Exploiting hierarchical context on a large database of object categories
    • Choi, M. J., Lim, J. J., Torralba, A., and Willsky, A. S. Exploiting hierarchical context on a large database of object categories. In CVPR, 2010.
    • (2010) CVPR
    • Choi, M.J.1    Lim, J.J.2    Torralba, A.3    Willsky, A.S.4
  • 15
    • 84933530882 scopus 로고
    • Approximating discrete probability distributions with dependence trees
    • Chow, C. and Liu, C. Approximating discrete probability distributions with dependence trees. IEEE Tran. on Information Theory, 14(3):462-467, 1968.
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    • Robust matrix decomposition with sparse corruptions
    • Hsu, D., Kakade, S. M., and Zhang, T. Robust matrix decomposition with sparse corruptions. IEEE Trans. on Inf. Theory, 57(11):7221-7234, 2011.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.