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Volumn 2015-January, Issue , 2015, Pages 3088-3096

Structured transforms for small-footprint deep learning

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION SCIENCE; MOBILE DEVICES;

EID: 84965177696     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (260)

References (25)
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    • Chen, G.1    Parada, C.2    Heigold, G.3
  • 6
    • 84965161536 scopus 로고    scopus 로고
    • Memory-bounded deep convolutional neural networks
    • M. D. Collins and P. Kohli. Memory-bounded deep convolutional neural networks. In ICASSP, 2013.
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    • Collins, M.D.1    Kohli, P.2
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    • Distilling the knowledge in a neural network
    • G. Hinton, O. Vinyals, and J. Dean. Distilling the knowledge in a neural network. In NIPS workshop, 2014.
    • (2014) NIPS Workshop
    • Hinton, G.1    Vinyals, O.2    Dean, J.3
  • 12
    • 21144451635 scopus 로고
    • Generalized displacement structure for block toeplitz, toeplitz block and toeplitz-derived matrices
    • T. Kailath and J. Chun. Generalized displacement structure for block toeplitz, toeplitz block and toeplitz-derived matrices. SIAM J. Matrix Anal. Appl., 15, 1994.
    • (1994) SIAM J. Matrix Anal. Appl. , vol.15
    • Kailath, T.1    Chun, J.2
  • 14
    • 0000665794 scopus 로고
    • Displacement structure: Theory and applications
    • T. Kailath and A. H. Sayed. Displacement structure: Theory and applications. SIAM Review, 37, 1995.
    • (1995) SIAM Review , vol.37
    • Kailath, T.1    Sayed, A.H.2
  • 15
    • 50249093806 scopus 로고    scopus 로고
    • An empirical evaluation of deep architectures on problems with many factors of variation
    • H. Larochelle, D. Erhan, A. C. Courville, J. Bergstra, and Y. Bengio. An empirical evaluation of deep architectures on problems with many factors of variation. In ICML, 2007.
    • (2007) ICML
    • Larochelle, H.1    Erhan, D.2    Courville, A.C.3    Bergstra, J.4    Bengio, Y.5
  • 16
    • 84897549944 scopus 로고    scopus 로고
    • Fastfood-approximating kernel expansions in loglinear time
    • Q. Le, T. Sarlos, and A. Smola. Fastfood-approximating kernel expansions in loglinear time. In ICML, 2013.
    • (2013) ICML
    • Le, Q.1    Sarlos, T.2    Smola, A.3
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    • 77953218689 scopus 로고    scopus 로고
    • Random features for large-scale kernel machines
    • A. Rahimi and B. Recht. Random features for large-scale kernel machines. In NIPS, 2007.
    • (2007) NIPS
    • Rahimi, A.1    Recht, B.2
  • 21
    • 84928966851 scopus 로고    scopus 로고
    • Fast multidimensional convolution in low-rank tensor formats via cross approximation
    • M. V. Rakhuba and I. V. Oseledets. Fast multidimensional convolution in low-rank tensor formats via cross approximation. SIAM J. Sci. Comput., 37, 2015.
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  • 22
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    • T. Sainath, B. Kingsbury, V. Sindhwani, E. Arisoy, and B. Ramabhadran. Low-rank matrix factorization for deep neural network training with high-dimensional output targets. In ICASSP, 2013.
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  • 23
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    • Convolutional neural networks for small-footprint keyword spotting
    • T. Sainath and C. Parada. Convolutional neural networks for small-footprint keyword spotting. In Proc. Interspeech, 2015.
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    • Sainath, T.1    Parada, C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.