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Volumn 35, Issue 8, 2013, Pages 1887-1901

Deep learning with hierarchical convolutional factor analysis

Author keywords

Bayesian; convolutional; deep learning; dictionary learning; factor analysis

Indexed keywords

BAYESIAN; CONVOLUTIONAL; DEEP LEARNING; DICTIONARY LEARNING; GIBBS SAMPLERS; MODEL PARAMETERS; ONLINE VERSIONS; VARIATIONAL BAYESIAN;

EID: 84879853859     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2013.19     Document Type: Article
Times cited : (100)

References (41)
  • 2
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • Nov
    • Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, "Gradient-Based Learning Applied to Document Recognition," Proc. IEEE, vol. 86, no. 11, pp. 2278-2324, Nov. 1998.
    • (1998) Proc. IEEE , vol.86 , Issue.11 , pp. 2278-2324
    • Lecun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 3
    • 33746600649 scopus 로고    scopus 로고
    • Reducing the dimensionality of data with neural networks
    • DOI 10.1126/science.1127647
    • G. Hinton and R. Salakhutdinov, "Reducing the Dimensionality of Data with Neural Networks," Science, vol. 313, no. 5786, pp. 504-507, 2006. (Pubitemid 44148451)
    • (2006) Science , vol.313 , Issue.5786 , pp. 504-507
    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 7
    • 71149119164 scopus 로고    scopus 로고
    • Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
    • H. Lee, R. Grosse, R. Ranganath, and A.Y. Ng, "Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations," Proc. Int'l Conf. Machine Learning, 2009.
    • (2009) Proc. Int'l Conf. Machine Learning
    • Lee, H.1    Grosse, R.2    Ranganath, R.3    Ng, A.Y.4
  • 8
    • 84863380535 scopus 로고    scopus 로고
    • Unsupervised feature learning for audio classification using convolutional deep belief networks
    • H. Lee, Y. Largman, P. Pham, and A. Ng, "Unsupervised Feature Learning for Audio Classification Using Convolutional Deep Belief Networks," Proc. Neural Information Processing Systems, 2009.
    • (2009) Proc. Neural Information Processing Systems
    • Lee, H.1    Largman, Y.2    Pham, P.3    Ng, A.4
  • 21
    • 0242295767 scopus 로고    scopus 로고
    • Bayesian factor regression models in the 'large p, small n' paradigm
    • J.M. Bernardo, M. Bayarri, J. Berger, A. Dawid, D. Heckerman, A. Smith, and M. West, eds Oxford Univ. Press
    • M. West, "Bayesian Factor Regression Models in the 'Large p, Small n' Paradigm," Bayesian Statistics 7, J.M. Bernardo, M. Bayarri, J. Berger, A. Dawid, D. Heckerman, A. Smith, and M. West, eds., pp. 723-732, Oxford Univ. Press, 2003.
    • (2003) Bayesian Statistics , vol.7 , pp. 723-732
    • West, M.1
  • 22
    • 62549125109 scopus 로고    scopus 로고
    • High-dimensional sparse factor modelling: Applications in gene expression genomics
    • C. Carvalho, J. Chang, J. Lucas, J.R. Nevins, Q. Wang, and M. West, "High-Dimensional Sparse Factor Modelling: Applications in Gene Expression Genomics," J. Am. Statistical Assoc., vol. 103, pp. 1438-1456, 2008.
    • (2008) J. Am. Statistical Assoc , vol.103 , pp. 1438-1456
    • Carvalho, C.1    Chang, J.2    Lucas, J.3    Nevins, J.R.4    Wang, Q.5    West, M.6
  • 23
    • 0001224048 scopus 로고    scopus 로고
    • Sparse bayesian learning and the relevance vector machine
    • DOI 10.1162/15324430152748236
    • M. Tipping, "Sparse Bayesian Learning and the Relevance Vector Machine," J. Machine Learning Research, vol. 1, pp. 211-244, 2001. (Pubitemid 33687203)
    • (2001) Journal of Machine Learning Research , vol.1 , Issue.3 , pp. 211-244
    • Tipping, M.E.1
  • 29
    • 84900510076 scopus 로고    scopus 로고
    • Non-negative matrix factorization with sparseness constraints
    • P.O. Hoyer, "Non-Negative Matrix Factorization with Sparseness Constraints," J. Machine Learning Research, vol. 5, pp. 1457-1469, 2004.
    • (2004) J. Machine Learning Research , vol.5 , pp. 1457-1469
    • Hoyer, P.O.1
  • 30
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • D.D. Lee and H.S. Seung, "Learning the Parts of Objects by Non-Negative Matrix Factorization," Nature, vol. 401, no. 6755 pp. 788-791, 1999.
    • (1999) Nature , vol.401 , Issue.6755 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 34


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.