메뉴 건너뛰기




Volumn , Issue , 2010, Pages

Layer-wise analysis of deep networks with Gaussian kernels

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

EID: 85161973295     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (15)

References (21)
  • 3
    • 33750713303 scopus 로고    scopus 로고
    • Accurate bounds for the eigenvalues of the kernel matrix
    • Nov.
    • Mikio L. Braun. Accurate bounds for the eigenvalues of the kernel matrix. Journal of Machine Learning Research, 7:2303-2328, Nov 2006.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 2303-2328
    • Braun, M.L.1
  • 5
    • 56449095373 scopus 로고    scopus 로고
    • A unified architecture for natural language processing: Deep neural networks with multitask learning
    • R. Collobert and J. Weston. A unified architecture for natural language processing: Deep neural networks with multitask learning. In International Conference on Machine Learning, ICML, 2008.
    • (2008) International Conference on Machine Learning, ICML
    • Collobert, R.1    Weston, J.2
  • 8
    • 33746600649 scopus 로고    scopus 로고
    • Reducing the dimensionality of data with neural networks
    • July
    • G. E. Hinton and R. R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504-507, July 2006.
    • (2006) Science , vol.313 , Issue.5786 , pp. 504-507
    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 9
    • 33745805403 scopus 로고    scopus 로고
    • A fast learning algorithm for deep belief nets
    • Geoffrey E. Hinton, Simon Osindero, and Yee-Whye Teh. A fast learning algorithm for deep belief nets. Neural Comput., 18(7):1527-1554, 2006.
    • (2006) Neural Comput. , vol.18 , Issue.7 , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2    Teh, Y.-W.3
  • 10
    • 33645410496 scopus 로고
    • Receptive fields, binocular interaction and functional architecture in the cat's visual cortex
    • January
    • D. H. Hubel and T. N. Wiesel. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. The Journal of physiology, 160:106-154, January 1962.
    • (1962) The Journal of Physiology , vol.160 , pp. 106-154
    • Hubel, D.H.1    Wiesel, T.N.2
  • 12
    • 59449087310 scopus 로고    scopus 로고
    • Exploring strategies for training deep neural networks
    • ISSN 1532-4435
    • Hugo Larochelle, Yoshua Bengio, Jérôme Louradour, and Pascal Lamblin. Exploring strategies for training deep neural networks. J. Mach. Learn. Res., 10:1-40, 2009. ISSN 1532-4435.
    • (2009) J. Mach. Learn. Res. , vol.10 , pp. 1-40
    • Larochelle, H.1    Bengio, Y.2    Louradour, J.3    Lamblin, P.4
  • 13
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • November
    • Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(1):2278-2324, November 1998.
    • (1998) Proceedings of the IEEE , vol.86 , Issue.1 , pp. 2278-2324
    • Lecun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 14
    • 71149084945 scopus 로고    scopus 로고
    • Deep learning from temporal coherence in video
    • Léon Bottou and Michael Littman, editors, Montreal, June. Omnipress
    • Hossein Mobahi, Ronan Collobert, and Jason Weston. Deep learning from temporal coherence in video. In Léon Bottou and Michael Littman, editors, Proceedings of the 26th International Conference on Machine Learning, pages 737-744, Montreal, June 2009. Omnipress.
    • (2009) Proceedings of the 26th International Conference on Machine Learning , pp. 737-744
    • Mobahi, H.1    Collobert, R.2    Weston, J.3
  • 15
    • 0028544395 scopus 로고
    • Network information criterion - Determining the number of hidden units for an artificial neural network model
    • Noboru Murata, Shuji Yoshizawa, and Shunichi Amari. Network information criterion - determining the number of hidden units for an artificial neural network model. IEEE Transactions on Neural Networks, 5:865-872, 1994.
    • (1994) IEEE Transactions on Neural Networks , vol.5 , pp. 865-872
    • Murata, N.1    Yoshizawa, S.2    Amari, S.3
  • 18
    • 0022471098 scopus 로고
    • Learning representations by back-propagating errors
    • D. E. Rumelhart, G. E. Hinton, and R. J. Williams. Learning representations by back-propagating errors. Nature, 323(6088):533-536, 1986.
    • (1986) Nature , vol.323 , Issue.6088 , pp. 533-536
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 19
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • Bernhard Schölkopf, Alexander Smola, and Klaus-Robert Müller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Comput., 10(5):1299-1319, 1998.
    • (1998) Neural Comput. , vol.10 , Issue.5 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.2    Müller, K.-R.3
  • 21
    • 0033670134 scopus 로고    scopus 로고
    • Engineering support vector machine kernels that recognize translation initiation sites
    • Alexander Zien, Gunnar Rätsch, Sebastian Mika, Bernhard Schölkopf, Thomas Lengauer, and Klaus-Robert Müller. Engineering support vector machine kernels that recognize translation initiation sites. Bioinformatics, 16(9):799-807, 2000.
    • (2000) Bioinformatics , vol.16 , Issue.9 , pp. 799-807
    • Zien, A.1    Rätsch, G.2    Mika, S.3    Schölkopf, B.4    Lengauer, T.5    Müller, K.-R.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.