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Volumn 2, Issue , 2012, Pages 1052-1060

Learning mixtures of tree graphical models

Author keywords

Graphical models; Mixture models; Spectral methods; Tree approximation

Indexed keywords

BOUNDED DEGREE GRAPHS; COMPUTATIONAL REQUIREMENTS; GRAPHICAL MODEL; MARKOV GRAPH; MIXTURE COMPONENTS; MIXTURE MODEL; SPECTRAL METHODS; TREE APPROXIMATION;

EID: 84877767001     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (55)

References (16)
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    • A. Jalali, C. Johnson, and P. Ravikumar. On learning discrete graphical models using greedy methods. In Proc. of NIPS, 2011.
    • (2011) Proc. of NIPS
    • Jalali, A.1    Johnson, C.2    Ravikumar, P.3
  • 3
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    • High-dimensional ising model selection using l1-regularized logistic regression
    • P. Ravikumar, M.J. Wainwright, and J. Lafferty. High-dimensional Ising Model Selection Using l1-Regularized Logistic Regression. Annals of Statistics, 2008.
    • (2008) Annals of Statistics
    • Ravikumar, P.1    Wainwright, M.J.2    Lafferty, J.3
  • 7
    • 0030588055 scopus 로고    scopus 로고
    • Full reconstruction of markov models on evolutionary trees: Identifiability and consistency
    • J.T. Chang. Full reconstruction of markov models on evolutionary trees: identifiability and consistency. Mathematical Biosciences, 137(1):51-73, 1996.
    • (1996) Mathematical Biosciences , vol.137 , Issue.1 , pp. 51-73
    • Chang, J.T.1
  • 8
    • 33746918412 scopus 로고    scopus 로고
    • Learning nonsingular phylogenies and hidden Markov models
    • E. Mossel and S. Roch. Learning nonsingular phylogenies and hidden Markov models. The Annals of Applied Probability, 16(2):583-614, 2006.
    • (2006) The Annals of Applied Probability , vol.16 , Issue.2 , pp. 583-614
    • Mossel, E.1    Roch, S.2
  • 10
    • 84933530882 scopus 로고
    • Approximating discrete probability distributions with dependence trees
    • C. Chow and C. Liu. Approximating Discrete Probability Distributions with Dependence Trees. IEEE Tran. on Information Theory, 14(3):462-467, 1968.
    • (1968) IEEE Tran. on Information Theory , vol.14 , Issue.3 , pp. 462-467
    • Chow, C.1    Liu, C.2
  • 11
    • 33747163541 scopus 로고    scopus 로고
    • High dimensional graphs and variable selection with the lasso
    • N. Meinshausen and P. Bühlmann. High Dimensional Graphs and Variable Selection With the Lasso. Annals of Statistics, 34(3):1436-1462, 2006.
    • (2006) Annals of Statistics , vol.34 , Issue.3 , pp. 1436-1462
    • Meinshausen, N.1    Bühlmann, P.2
  • 16
    • 79951910784 scopus 로고    scopus 로고
    • A large-deviation analysis for the maximum likelihood learning of tree structures
    • March
    • V.Y.F. Tan, A. Anandkumar, and A. Willsky. A Large-Deviation Analysis for the Maximum Likelihood Learning of Tree Structures. IEEE Tran. on Information Theory, 57(3):1714-1735, March 2011.
    • (2011) IEEE Tran. on Information Theory , vol.57 , Issue.3 , pp. 1714-1735
    • Tan, V.Y.F.1    Anandkumar, A.2    Willsky, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.