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Volumn 69, Issue 7-9 SPEC. ISS., 2006, Pages 825-837

Hidden neuron pruning of multilayer perceptrons using a quantified sensitivity measure

Author keywords

Multilayer perceptron; Neural network; Neuron pruning; Relevance measure; Sensitivity measure

Indexed keywords

COMPUTATIONAL COMPLEXITY; ITERATIVE METHODS; NEUROPHYSIOLOGY; SENSITIVITY ANALYSIS;

EID: 32544452874     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2005.04.010     Document Type: Article
Times cited : (91)

References (23)
  • 3
    • 0026625982 scopus 로고
    • Sensitivity analysis of multilayer perceptron with differentiable activation functions
    • J.Y. Choi C.H. Choi Sensitivity analysis of multilayer perceptron with differentiable activation functions IEEE Trans. Neural Networks 3 1 1992 101-107
    • (1992) IEEE Trans. Neural Networks , vol.3 , Issue.1 , pp. 101-107
    • Choi, J.Y.1    Choi, C.H.2
  • 5
    • 0035505658 scopus 로고    scopus 로고
    • A new pruning heuristic based on variance analysis of sensitivity information
    • A.P. Engelbrecht A new pruning heuristic based on variance analysis of sensitivity information IEEE Trans. Neural Networks 12 6 2001 1386-1398
    • (2001) IEEE Trans. Neural Networks , vol.12 , Issue.6 , pp. 1386-1398
    • Engelbrecht, A.P.1
  • 8
    • 0028413960 scopus 로고
    • A simple and effective method for removal of hidden units and weights
    • M. Hagiwara A simple and effective method for removal of hidden units and weights Neurocomputing 6 1994 207-218
    • (1994) Neurocomputing , vol.6 , pp. 207-218
    • Hagiwara, M.1
  • 9
    • 0001234705 scopus 로고
    • Second-order derivatives for network pruning: Optimal brain surgeon
    • C.L. Giles, S.J. Hanson, J.D. Cowan (Eds.)
    • B. Hassibi, D.G. Stork, Second-order derivatives for network pruning: Optimal brain surgeon, in: C.L. Giles, S.J. Hanson, J.D. Cowan (Eds.), Proceedings of the Neural Information Processing Systems, vol. 5, 1992, pp. 164-171.
    • (1992) Proceedings of the Neural Information Processing Systems , vol.5 , pp. 164-171
    • Hassibi, B.1    Stork, D.G.2
  • 11
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • K.M. Hornik M. Stinchcombea H. White Multilayer feedforward networks are universal approximators Neural Networks 2 1989 359-366
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik, K.M.1    Stinchcombea, M.2    White, H.3
  • 12
    • 0025447562 scopus 로고
    • A simple procedure for pruning back-propagation trained neural networks
    • E.D. Karnin A simple procedure for pruning back-propagation trained neural networks IEEE Trans. Neural Networks 1 2 1990 239-242
    • (1990) IEEE Trans. Neural Networks , vol.1 , Issue.2 , pp. 239-242
    • Karnin, E.D.1
  • 13
    • 0031146959 scopus 로고    scopus 로고
    • Constructive algorithms for structure learning in feedforward neural networks for regression problems
    • T.Y. Kwok D.Y. Yeung Constructive algorithms for structure learning in feedforward neural networks for regression problems IEEE Trans. Neural Networks 8 3 1997 630-645
    • (1997) IEEE Trans. Neural Networks , vol.8 , Issue.3 , pp. 630-645
    • Kwok, T.Y.1    Yeung, D.Y.2
  • 14
    • 0000900876 scopus 로고
    • Skeletonization: A technique for trimming the fat from a network via relevance assessment
    • D.S. Touretzky (Ed.)
    • M.C. Mozer, P. Smolensky, Skeletonization: A technique for trimming the fat from a network via relevance assessment, in: D.S. Touretzky (Ed.), Proceedings of the Neural Information Processing Systems, vol. 1, 1989, pp. 107-115.
    • (1989) Proceedings of the Neural Information Processing Systems , vol.1 , pp. 107-115
    • Mozer, M.C.1    Smolensky, P.2
  • 16
    • 85156214178 scopus 로고    scopus 로고
    • Pruning with generalization based weight saliencies: γ OBD, γ OBS
    • D.S. Touretzky, M.C. Mozer, M.E. Hasselmo (Eds.)
    • M.W. Pedersen, L.K. Hansen, J. Larsen, Pruning with generalization based weight saliencies: γ OBD, γ OBS, in: D.S. Touretzky, M.C. Mozer, M.E. Hasselmo (Eds.), Proceedings of the Neural Information Processing Systems, vol. 8, 1996, pp. 521-528.
    • (1996) Proceedings of the Neural Information Processing Systems , vol.8 , pp. 521-528
    • Pedersen, M.W.1    Hansen, L.K.2    Larsen, J.3
  • 17
    • 0027662338 scopus 로고
    • Pruning algorithms - A survey
    • R. Reed Pruning algorithms - a survey IEEE Trans. Neural Networks 4 5 1993 740-747
    • (1993) IEEE Trans. Neural Networks , vol.4 , Issue.5 , pp. 740-747
    • Reed, R.1
  • 19
    • 0026017007 scopus 로고
    • Creating artificial neural networks that generalize
    • J. Sietsma R.J.F. Dow Creating artificial neural networks that generalize Neural Networks 4 1991 67-79
    • (1991) Neural Networks , vol.4 , pp. 67-79
    • Sietsma, J.1    Dow, R.J.F.2
  • 20
    • 0035251045 scopus 로고    scopus 로고
    • A simple neural network pruning algorithm with application to filter synthesis
    • K. Suzuki I. Horiba N. Sugie A simple neural network pruning algorithm with application to filter synthesis Neural Process. Lett. 13 1 2001 43-53
    • (2001) Neural Process. Lett. , vol.13 , Issue.1 , pp. 43-53
    • Suzuki, K.1    Horiba, I.2    Sugie, N.3
  • 21
    • 0007778387 scopus 로고
    • Node splitting: A constructive algorithm for feedforward neural networks
    • J. Moody, S. Hanson, R. Lippmann (Eds.)
    • M. Wynne-Jones, Node splitting: A constructive algorithm for feedforward neural networks, in: J. Moody, S. Hanson, R. Lippmann (Eds.), Proceedings of the Neural Information Processing Systems, vol. 4, 1992, pp. 1072-1079.
    • (1992) Proceedings of the Neural Information Processing Systems , vol.4 , pp. 1072-1079
    • Wynne-Jones, M.1
  • 22
    • 0037264956 scopus 로고    scopus 로고
    • A quantified sensitivity measure for multilayer perceptron to input perturbation
    • X. Zeng D.S. Yeung A quantified sensitivity measure for multilayer perceptron to input perturbation Neural Comput. 15 1 2003 183-212
    • (2003) Neural Comput. , vol.15 , Issue.1 , pp. 183-212
    • Zeng, X.1    Yeung, D.S.2
  • 23
    • 0031553665 scopus 로고    scopus 로고
    • Perturbation method for deleting redundant inputs of perceptron networks
    • J.M. Zurada A. Malinowski S. Usui Perturbation method for deleting redundant inputs of perceptron networks Neurocomputing 14 1997 177-193
    • (1997) Neurocomputing , vol.14 , pp. 177-193
    • Zurada, J.M.1    Malinowski, A.2    Usui, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.