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Volumn , Issue , 2014, Pages 17-22

Fast learning for big data applications using parameterized multilayer perceptron

Author keywords

Backpropagation; Multilayer perceptron; Steepest descent rule

Indexed keywords

BIG DATA; CLASSIFICATION (OF INFORMATION); MATRIX ALGEBRA; MULTILAYER NEURAL NETWORKS; MULTILAYERS; PARAMETERIZATION;

EID: 84921749046     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BigData.2014.7004351     Document Type: Conference Paper
Times cited : (4)

References (15)
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    • Hinton, G.1    Osindero, S.2    Teh, Y.-W.3
  • 6
    • 85172623915 scopus 로고    scopus 로고
    • http://www.iro.umontreal.ca/~lisa/twiki/bin/view.cgi/ Public/MnistVariations
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    • 85172636005 scopus 로고    scopus 로고
    • http://yann.lecun.com/exdb/mnist/
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    • Effect of number of hidden neurons on learning in large-scale layered neural networks
    • IEEE
    • Shibata, Katsunari, and Yusuke Ikeda. "Effect of number of hidden neurons on learning in large-scale layered neural networks." ICCAS-SICE, 2009. IEEE, 2009.
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    • Shibata, K.1    Ikeda, Y.2
  • 11
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    • Classification of EEG signals using neural network and logistic regression
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    • Subasi, A.1    Erçelebi, E.2
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    • Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
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    • Vincent, P.1
  • 14
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    • Neural-network-based decentralized adaptive output-feedback control for large-scale stochastic nonlinear systems
    • Zhou, Qi, et al. "Neural-network-based decentralized adaptive output-feedback control for large-scale stochastic nonlinear systems." Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on 42.6 (2012): 1608-1619.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.