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Volumn 207, Issue , 2006, Pages 265-296

High dimensional classification with bayesian neural networks and dirichlet diffusion trees

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EID: 34047138821     PISSN: 14349922     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-35488-8_11     Document Type: Article
Times cited : (20)

References (16)
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    • Lampinen, J.1    Vehtari, A.2
  • 8
    • 0028698662 scopus 로고
    • Bayesian non-linear modeling for the energy prediction competition
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    • (1994) ASHRAE Transactions , vol.100 , Issue.PART. 2 , pp. 1053-1062
    • MacKay, D.J.C.1
  • 9
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    • Probabilistic Inference Using Markov Chain Monte Carlo Methods
    • Technical Report CRG-TR-93-1, Department of Computer Science, University of Toronto, 144 pages. Available from
    • Neal, R. M. (1993) Probabilistic Inference Using Markov Chain Monte Carlo Methods, Technical Report CRG-TR-93-1, Department of Computer Science, University of Toronto, 144 pages. Available from http://www.cs.utoronto.ca/ ~radford/.
    • (1993)
    • Neal, R.M.1
  • 10
    • 0003301456 scopus 로고    scopus 로고
    • Bayesian Learning for Neural Networks
    • Springer-Verlag
    • Neal, R. M. (1996) Bayesian Learning for Neural Networks, Lecture Notes in Statistics No. 118, Springer-Verlag.
    • (1996) Lecture Notes in Statistics , Issue.118
    • Neal, R.M.1
  • 11
    • 0001854616 scopus 로고    scopus 로고
    • Assessing relevance determination methods using DELVE
    • C. M. Bishop editor, Springer-Verlag
    • Neal, R. M. (1998) "Assessing relevance determination methods using DELVE", in C. M. Bishop (editor) Neural Networks and Machine Learning, pp. 97-129, Springer-Verlag.
    • (1998) Neural Networks and Machine Learning , pp. 97-129
    • Neal, R.M.1
  • 12
    • 0002628667 scopus 로고    scopus 로고
    • Regression and classification using Gaussian process priors (with discussion)
    • J. M. Bernardo, et al editors, Oxford University Press, pp
    • Neal, R. M. (1999) "Regression and classification using Gaussian process priors" (with discussion), in J. M. Bernardo, et al (editors) Bayesian Statistics 6, Oxford University Press, pp. 475-501.
    • (1999) Bayesian Statistics 6 , pp. 475-501
    • Neal, R.M.1
  • 13
    • 33748700867 scopus 로고    scopus 로고
    • Defining priors for distributions using Dirichlet diffusion trees
    • Technical Report No. 0104, Dept. of Statistics, University of Toronto, 25 pages
    • Neal, R. M. (2001) "Defining priors for distributions using Dirichlet diffusion trees", Technical Report No. 0104, Dept. of Statistics, University of Toronto, 25 pages.
    • (2001)
    • Neal, R.M.1
  • 14
    • 31844452656 scopus 로고    scopus 로고
    • Density modeling and clustering using Dirichlet diffusion trees
    • J. M. Bernardo, et al, editors, Oxford University Press
    • Neal, R. M. (2003) "Density modeling and clustering using Dirichlet diffusion trees", in J. M. Bernardo, et al. (editors) Bayesian Statistics 7, pp. 619-629, Oxford University Press.
    • (2003) Bayesian Statistics 7 , pp. 619-629
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  • 15
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    • Rasmussen, C. E. (199G) Evaluation of Gaussian Processes and Other Methods for Non-linear Regression, PhD Thesis, Dept. of Computer Science, University of Toronto.
  • 16
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    • Rumelhart, D. E., Hinton, G. E., and Williams, R. J. (1986) Learning internal representations by error propagation, in D. E. Rumelhart and J. L. McClelland (editors) Parallel Distributed Processing: Explorations in the Micro structure of Cognition, 1: Foundations, Cambridge, Massachusetts: MIT Press.
    • Rumelhart, D. E., Hinton, G. E., and Williams, R. J. (1986) "Learning internal representations by error propagation", in D. E. Rumelhart and J. L. McClelland (editors) Parallel Distributed Processing: Explorations in the Micro structure of Cognition, Volume 1: Foundations, Cambridge, Massachusetts: MIT Press.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.