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Volumn , Issue , 2014, Pages

An empirical analysis of dropout in piecewise linear networks

Author keywords

[No Author keywords available]

Indexed keywords

MAXIMUM LIKELIHOOD; PIECEWISE LINEAR TECHNIQUES;

EID: 85083951533     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (20)

References (25)
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    • ImageNet classification with deep convolutional neural networks
    • Krizhevsky, A., Sutskever, I., and Hinton, G. (2012b). ImageNet classification with deep convolutional neural networks. In NIPS’2012.
    • (2012) NIPS’2012
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.3
  • 15
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11), 2278–2324.
    • (1998) Proceedings of the IEEE , vol.86 , Issue.11 , pp. 2278-2324
    • LeCun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 18
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    • The strength of weak learnability
    • Schapire, R. E. (1990). The strength of weak learnability. Machine Learning, 5(2), 197–227.
    • (1990) Machine Learning , vol.5 , Issue.2 , pp. 197-227
    • Schapire, R.E.1
  • 20
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    • Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
    • Vincent, P., Larochelle, H., Lajoie, I., Bengio, Y., and Manzagol, P.-A. (2010). Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion. Journal of Machine Learning Research, 11, 3371–3408.
    • (2010) Journal of Machine Learning Research , vol.11 , pp. 3371-3408
    • Vincent, P.1    Larochelle, H.2    Lajoie, I.3    Bengio, Y.4    Manzagol, P.-A.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.