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Volumn , Issue , 2013, Pages

Adaptive dropout for training deep neural networks

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS;

EID: 84896515095     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (348)

References (21)
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    • Hinton, G.E.1    Osindero, S.2    Teh, Y.W.3
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    • 33746600649 scopus 로고    scopus 로고
    • Reducing the dimensionality of data with neural networks
    • G.E. Hinton and R.R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504-507, 2006.
    • (2006) Science , vol.313 , Issue.5786 , pp. 504-507
    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 13
    • 77956509090 scopus 로고    scopus 로고
    • Rectified linear units improve restricted boltzmann machines
    • Omnipress Madison, WI
    • V. Nair and G.E. Hinton. Rectified linear units improve restricted boltzmann machines. In Proc. 27th International Conference on Machine Learning, pages 807-814. Omnipress Madison, WI, 2010.
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    • Nair, V.1    Hinton, G.E.2
  • 16
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    • Creating artificial neural networks that generalize
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    • Sietsma, J.1    Dow, R.J.F.2
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    • Nonparametric guidance of autoencoder representations using label information
    • Jasper Snoek, Ryan P Adams, and Hugo Larochelle. Nonparametric guidance of autoencoder representations using label information. Journal of Machine Learning Research, 13:2567- 2588, 2012.
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    • Snoek, J.1    Ryan, P.A.2    Larochelle, H.3
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    • Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
    • P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P.A. Manzagol. Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion. The Journal of Machine Learning Research, 11:3371-3408, 2010.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.