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Volumn , Issue , 2011, Pages 1201-1208

On autoencoders and score matching for energy based models

Author keywords

[No Author keywords available]

Indexed keywords

AUTOENCODERS; CLASSIFICATION PERFORMANCE; CLASSIFICATION RESULTS; CONDITIONAL DISTRIBUTION; ENERGY-BASED MODELS; ESTIMATION METHODS; GAUSSIANS; IMAGE DE-NOISING; MAXIMUM LIKELIHOOD ESTIMATOR; REGULARIZATION FUNCTION; STOCHASTIC APPROXIMATIONS; TRAINING METHODS;

EID: 80053450846     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (69)

References (25)
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  • 4
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    • A fast learning algorithm for deep belief nets
    • DOI 10.1162/neco.2006.18.7.1527
    • Hinton, G.E., Osindero, S., and Teh, Y.W. A fast learning algorithm for deep belief nets. Neural Computation, 18(7):1527-1554, 2006. (Pubitemid 44024729)
    • (2006) Neural Computation , vol.18 , Issue.7 , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2    Teh, Y.-W.3
  • 5
    • 22044434800 scopus 로고    scopus 로고
    • Estimation of non-normalized statistical models using score matching
    • Hyvärinen, A. Estimation of non-normalized statistical models using score matching. Journal of Machine Learning Research, 6:695-709, 2005.
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 695-709
    • Hyvärinen, A.1
  • 10
    • 77953520240 scopus 로고    scopus 로고
    • Learning to represent spatial transformations with factored higher-order Boltzmann machines
    • Memisevic, R. and Hinton, G.E. Learning to represent spatial transformations with factored higher-order Boltzmann machines. Neural Computation, 22:1473-1492, 2009.
    • (2009) Neural Computation , vol.22 , pp. 1473-1492
    • Memisevic, R.1    Hinton, G.E.2
  • 11
    • 77955989954 scopus 로고    scopus 로고
    • Modeling pixel means and covariances using factorized third-order Boltzmann machines
    • Ranzato, M. and Hinton, G.E. Modeling pixel means and covariances using factorized third-order Boltzmann machines. In IEEE Computer Vision and Pattern Recognition, pp. 2551-2558, 2010.
    • (2010) IEEE Computer Vision and Pattern Recognition , pp. 2551-2558
    • Ranzato, M.1    Hinton, G.E.2
  • 16
    • 77952681438 scopus 로고    scopus 로고
    • A tutorial on stochastic approximation algorithms for training restricted Boltzmann machines and deep belief nets
    • Swersky, K., Chen, B., Marlin, B.M., and De Freitas, N. A tutorial on stochastic approximation algorithms for training restricted Boltzmann machines and deep belief nets. In Information Theory and Applications Workshop, pp. 1-10, 2010.
    • (2010) Information Theory and Applications Workshop , pp. 1-10
    • Swersky, K.1    Chen, B.2    Marlin, B.M.3    De Freitas, N.4
  • 18
    • 56449086223 scopus 로고    scopus 로고
    • Training restricted Boltzmann machines using approximations to the likelihood gradient
    • Tieleman, T. Training restricted Boltzmann machines using approximations to the likelihood gradient. In International Conference on Machine Learning, pp. 1064-1071, 2008.
    • (2008) International Conference on Machine Learning , pp. 1064-1071
    • Tieleman, T.1
  • 21
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    • A connection between score matching and denoising autoencoders
    • To appear
    • Vincent, P. A connection between score matching and denoising autoencoders. Neural Computation, To appear, 2011.
    • (2011) Neural Computation
    • Vincent, P.1
  • 25
    • 0000355193 scopus 로고
    • Parametric inference for imperfectly observed Gibbsian fields
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    • Younes, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.