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Volumn 22, Issue , 2012, Pages 1287-1294

A hybrid neural network-latent topic model

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

EID: 84954233874     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper
Times cited : (28)

References (21)
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    • A Bayesian hierarchical model for learning natural scene categories
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  • 7
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    • A fast learning algorithm for deep belief nets
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    • Hinton, G.E.1    Osindero, S.2
  • 8
    • 33746600649 scopus 로고    scopus 로고
    • Reducing the dimensionality of data with neural networks
    • July
    • G. E. Hinton and R. R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504-507, July 2006.
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    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 9
    • 0034818212 scopus 로고    scopus 로고
    • Unsupervised learning by probabilistic latent semantic analysis
    • T. Hofmann. Unsupervised learning by probabilistic latent semantic analysis. In Machine Learning, page 2001, 2001.
    • (2001) Machine Learning , pp. 2001
    • Hofmann, T.1
  • 11
    • 79957489009 scopus 로고    scopus 로고
    • Disclda: Discriminative learning for dimensionality reduction and classification
    • S. Lacoste-Julien, F. Sha, and M. Jordan. Disclda: Discriminative learning for dimensionality reduction and classification. In NIPS, 2009.
    • (2009) NIPS
    • Lacoste-Julien, S.1    Sha, F.2    Jordan, M.3
  • 12
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    • Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories
    • S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In CVPR, pages 2169-2178, 2006.
    • (2006) CVPR , pp. 2169-2178
    • Lazebnik, S.1    Schmid, C.2    Ponce, J.3
  • 13
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-based learning applied to document recognition. IEEE, 86(11):2278-24, 1998.
    • (1998) IEEE , vol.86 , Issue.11 , pp. 2278-2324
    • LeCun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 14
    • 71149119164 scopus 로고    scopus 로고
    • Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
    • H. Lee, R. Grosse, R. Ranganath, and A. Y. Ng. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. In ICML, pages 609-616, 2009.
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  • 15
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    • Distinctive image features from scaleinvariant keypoints
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  • 17
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    • Modeling pixel means and covariances using factorized thirdorder Boltzmann Machines
    • M. Ranzato and G. Hinton. Modeling pixel means and covariances using factorized thirdorder Boltzmann Machines. In CVPR, 2010.
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  • 19
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    • Using deep belief nets to learn covariance kernels for Gaussian processes
    • R. Salakhutdinov and G. E. Hinton. Using deep belief nets to learn covariance kernels for gaussian processes. In NIPS, 2008.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.