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Volumn , Issue , 2009, Pages 1145-1152

Implicit mixtures of Restricted Boltzmann machines

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS;

EID: 84858768016     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (69)

References (13)
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    • Hinton, G.E.1
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    • 33746600649 scopus 로고    scopus 로고
    • Reducing the dimensionality of data with neural networks
    • DOI 10.1126/science.1127647
    • G. E. Hinton and R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313:504-507, 2006. (Pubitemid 44148451)
    • (2006) Science , vol.313 , Issue.5786 , pp. 504-507
    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 7
    • 5044231640 scopus 로고    scopus 로고
    • Learning methods for generic object recognition with invariance to pose and lighting
    • Washington, D.C.
    • Y. LeCun, F. J. Huang, and L. Bottou. Learning methods for generic object recognition with invariance to pose and lighting. In CVPR, Washington, D.C., 2004.
    • (2004) CVPR
    • Lecun, Y.1    Huang, F.J.2    Bottou, L.3
  • 8
    • 24644467818 scopus 로고    scopus 로고
    • Fields of experts: A framework for learning image priors
    • S. Roth and M. J. Black. Fields of experts: A framework for learning image priors. In CVPR, pages 860-867, 2005.
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    • Roth, S.1    Black, M.J.2
  • 9
    • 50949124472 scopus 로고    scopus 로고
    • Steerable random fields
    • S. Roth and M. J. Black. Steerable random fields. In ICCV, 2007.
    • (2007) ICCV
    • Roth, S.1    Black, M.J.2
  • 10
    • 85162047295 scopus 로고    scopus 로고
    • Representational power of restricted boltzmann machines and deep belief networks
    • To appear
    • N. Le Roux and Y. Bengio. Representational power of restricted boltzmann machines and deep belief networks. Neural Computation, To appear.
    • Neural Computation
    • Le Roux, N.1    Bengio, Y.2
  • 11
    • 56449102578 scopus 로고    scopus 로고
    • On the quantitative analysis of deep belief networks
    • Helsinki
    • R. Salakhutdinov and I. Murray. On the quantitative analysis of deep belief networks. In ICML, Helsinki, 2008.
    • (2008) ICML
    • Salakhutdinov, R.1    Murray, I.2
  • 12
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    • Deep narrow sigmoid belief networks are universal approximators
    • To appear
    • I. Sutskever and G. E. Hinton. Deep narrow sigmoid belief networks are universal approximators. Neural Computation, To appear.
    • Neural Computation
    • Sutskever, I.1    Hinton, G.E.2
  • 13
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    • Exponential family harmoniums with an application to information retrieval
    • M. Welling, M. Rosen-Zvi, and G. E. Hinton. Exponential family harmoniums with an application to information retrieval. In NIPS 17, 2005.
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    • Welling, M.1    Rosen-Zvi, M.2    Hinton, G.E.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.