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Volumn , Issue , 2009, Pages 1303-1311

Which graphical models are difficult to learn?

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; MARKOV PROCESSES;

EID: 84858782866     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (78)

References (17)
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  • 4
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  • 5
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    • Consistent estimation of the basic neighborhood structure of Markov random fields
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  • 6
    • 0002219642 scopus 로고    scopus 로고
    • Learning Bayesian network structure from massive datasets: The sparse candidate algorithm
    • N. Friedman, I. Nachman, and D. Peer, "Learning Bayesian network structure from massive datasets: The sparse candidate algorithm". In UAI, 1999.
    • (1999) UAI
    • Friedman, N.1    Nachman, I.2    Peer, D.3
  • 8
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    • Inferring graphical model structure using l1-regularized pseudolikelihood
    • M. Wainwright, P. Ravikumar, and J. Lafferty, "Inferring graphical model structure using l1-regularized pseudolikelihood", In NIPS, 2006.
    • (2006) NIPS
    • Wainwright, M.1    Ravikumar, P.2    Lafferty, J.3
  • 9
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    • Estimation of sparse binary pairwise Markov networks using pseudo-likelihoods
    • H. Höfling and R. Tibshirani, "Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods", Journal of Machine Learning Research, 2009, Vol. 10, 883-906.
    • (2009) Journal of Machine Learning Research , vol.10 , pp. 883-906
    • Höfling, H.1    Tibshirani, R.2
  • 10
    • 41549101939 scopus 로고    scopus 로고
    • Model selection through sparse maximum likelihood estimation for multivariate Gaussian or binary data
    • March
    • O. Banerjee, L. El Ghaoui and A. d'Aspremont, "Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data", Journal of Machine Learning Research, March 2008, Vol. 9, 485-516.
    • (2008) Journal of Machine Learning Research , vol.9 , pp. 485-516
    • Banerjee, O.1    El Ghaoui, L.2    D'Aspremont, A.3
  • 11
    • 33645035051 scopus 로고    scopus 로고
    • Model selection and estimation in regression with grouped variables
    • M. Yuan and Y. Lin, "Model Selection and Estimation in Regression with Grouped Variables", J. Royal. Statist. Soc B, 2006, 68, Vol. 19, 49-67.
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  • 12
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    • High dimensional graphs and variable selection with the lasso
    • N. Meinshausen and P. Büuhlmann, "High dimensional graphs and variable selection with the lasso", Annals of Statistics, 2006, 34, Vol. 3.
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    • Meinshausen, N.1    Büuhlmann, P.2
  • 15
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    • Critical behavior of the bond-dilute two-dimensional ising model
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    • Critical temperatures of anisotropic ising lattices. II. General upper bounds
    • Oct.
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  • 17
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    • Ising models on locally tree like graphs
    • to appear, arXiv:0804.4726v2 [math.PR]
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    • Dembo, A.1    Montanari, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.