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Volumn 8131 LNCS, Issue , 2013, Pages 106-113

A two-stage pretraining algorithm for deep boltzmann machines

Author keywords

Deep Boltzmann Machine; Deep Learning; Pretraining

Indexed keywords

DEEP BOLTZMANN MACHINES; DEEP LEARNING; GENERATIVE MODEL; MARKOV RANDOM FIELD MODEL; POSTERIOR DISTRIBUTIONS; PRE-TRAINING; RESTRICTED BOLTZMANN MACHINE; STOCHASTIC GRADIENT;

EID: 84884941662     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40728-4_14     Document Type: Conference Paper
Times cited : (20)

References (16)
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    • Hinton, G., Salakhutdinov, R.: Reducing the dimensionality of data with neural networks. Science 313(5786), 504-507 (2006)
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    • Hinton, G.1    Salakhutdinov, R.2
  • 6
    • 0013344078 scopus 로고    scopus 로고
    • Training products of experts by minimizing contrastive divergence
    • Hinton, G.: Training products of experts by minimizing contrastive divergence. Neural Computation 14, 1771-1800 (2002)
    • (2002) Neural Computation , vol.14 , pp. 1771-1800
    • Hinton, G.1
  • 9
    • 84872571941 scopus 로고    scopus 로고
    • In: Montavon, G., Orr, G.B.,Müller, K.-R. (eds.) NN: Tricks of the Trade, 2nd edn. LNCS Springer, Heidelberg
    • Montavon, G., Müller, K.-R.: Deep Boltzmann machines and the centering trick. In: Montavon, G., Orr, G.B.,Müller, K.-R. (eds.) NN: Tricks of the Trade, 2nd edn. LNCS, vol. 7700, pp. 621-637. Springer, Heidelberg (2012)
    • (2012) Deep Boltzmann Machines and the Centering Trick , vol.7700 , pp. 621-637
    • Montavon, G.1    Müller, K.-R.2
  • 12
    • 77956506016 scopus 로고    scopus 로고
    • In: Fürnkranz, J., Joachims, T. (eds.) Proc. of the 27th Int. Conf. on Machine Learning (ICML 2010) Omnipress, Haifa
    • Salakhutdinov, R.: Learning deep Boltzmann machines using adaptive MCMC. In: Fürnkranz, J., Joachims, T. (eds.) Proc. of the 27th Int. Conf. on Machine Learning (ICML 2010), pp. 943-950. Omnipress, Haifa (2010)
    • (2010) Learning Deep Boltzmann Machines using Adaptive MCMC , pp. 943-950
    • Salakhutdinov, R.1
  • 16
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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.,Manzagol, P.A.: Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion. Journal of Machine Learning Research 11, 3371-3408 (2010)
    • (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.