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Volumn , Issue , 2002, Pages

Thin junction trees

Author keywords

[No Author keywords available]

Indexed keywords

FORESTRY; ITERATIVE METHODS;

EID: 84899032200     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (56)

References (16)
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    • Bodlaender, H.1
  • 2
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    • Approximating discrete probability distributions with dependence trees
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    • Chow, C.K.1    Liu, C.N.2
  • 3
    • 0000913324 scopus 로고    scopus 로고
    • SVMTORCH: Support vector machines for large-scale regression problems
    • R. Collobert and S. Bengio, SVMTorch: support vector machines for large-scale regression problems, Journal of Machine Learning Research, 1, 143-160, 2001.
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    • Collobert, R.1    Bengio, S.2
  • 5
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    • I-divergence geometry of probability distributions and minimization problems
    • I. Csiszar, I-divergence geometry of probability distributions and minimization problems, Annals of Probability, 3, 146-158, 1975.
    • (1975) Annals of Probability , vol.3 , pp. 146-158
    • Csiszar, I.1
  • 6
    • 0001573124 scopus 로고
    • Generalized iterative scaling for log-linear models
    • J.N. Darroch and D. Ratcliff, Generalized iterative scaling for log-linear models, Ann. Math. Statist., 43, 1470-1480, 1972.
    • (1972) Ann. Math. Statist , vol.43 , pp. 1470-1480
    • Darroch, J.N.1    Ratcliff, D.2
  • 7
    • 0036161034 scopus 로고    scopus 로고
    • Training invariant support vector machines
    • D. DeCoste and B. Scholkopf, Training invariant support vector machines, Machine Learning, 46, 1-3, 2002.
    • (2002) Machine Learning , vol.46 , pp. 1-3
    • De Coste, D.1    Scholkopf, B.2
  • 8
    • 34249761849 scopus 로고
    • Learning bayesian networks: The combination of knowledge and statistical data
    • D. Heckerman, D. Geiger, and D.M. Chickering, Learning Bayesian networks: The combination of knowledge and statistical data, Machine Learning, 20, 197-243, 1995.
    • (1995) Machine Learning , vol.20 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.M.3
  • 10
    • 0003641246 scopus 로고
    • On the effective implementation of the iterative proportional fitting procedure
    • R. Jirousek and S. Preucil, On the effective implementation of the iterative proportional fitting procedure, Computational Statistics and Data Analysis, 19, 177-189, 1995.
    • (1995) Computational Statistics and Data Analysis , vol.19 , pp. 177-189
    • Jirousek, R.1    Preucil, S.2
  • 11
  • 12
    • 84898935589 scopus 로고    scopus 로고
    • Y. Le Cun, http://www.research.att.com/yann/exdb/mnist/index.html.
    • Cun, Y.L.1
  • 13
    • 84898988919 scopus 로고    scopus 로고
    • Recognizing hand-written digits using hierarchical products of experts
    • MIT Press, Cambridge, MA
    • G. Mayraz and G. Hinton, Recognizing hand-written digits using hierarchical products of experts, Adv. NIPS 13, MIT Press, Cambridge, MA, 2001.
    • (2001) Adv. NIPS , vol.13
    • Mayraz, G.1    Hinton, G.2
  • 15
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    • Maximum likelihood bounded tree-width markov networks
    • N. Srebro, Maximum likelihood bounded tree-width Markov networks, in UAI 2001.
    • (2001) UAI
    • Srebro, N.1
  • 16
    • 0000806445 scopus 로고    scopus 로고
    • Minimax entropy principle and its application to texture modeling
    • S.C. Zhu, Y.W. Wu, and D. Mumford, Minimax entropy principle and its application to texture modeling, Neural Computation, 9, 1997.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.