메뉴 건너뛰기




Volumn 12, Issue 8, 2000, Pages 1889-1900

Gradient-based optimization of hyperparameters

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE;

EID: 0034241361     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976600300015187     Document Type: Article
Times cited : (558)

References (21)
  • 2
    • 0002906163 scopus 로고
    • Improving the convergence of back-propagation learning with second order methods
    • D. Touretzky, G. Hinton, & T. Sejnowski (Eds.), San Mateo, CA: Morgan Kaufmann
    • Becker, S., & LeCun, Y. (1989). Improving the convergence of back-propagation learning with second order methods. In D. Touretzky, G. Hinton, & T. Sejnowski (Eds.), Proceedings of the 1988 Connectionist Models Summer School (pp. 29-37). San Mateo, CA: Morgan Kaufmann.
    • (1989) Proceedings of the 1988 Connectionist Models Summer School , pp. 29-37
    • Becker, S.1    LeCun, Y.2
  • 4
    • 0011805758 scopus 로고
    • Exact calculation of the Hessian matrix for the multi-layer perceptron
    • Bishop, C. (1992). Exact calculation of the Hessian matrix for the multi-layer perceptron. Neural Computation, 4, 494-501.
    • (1992) Neural Computation , vol.4 , pp. 494-501
    • Bishop, C.1
  • 5
    • 0013309537 scopus 로고    scopus 로고
    • Online algorithms and stochastic approximations
    • D. Saad (Ed.), Cambridge: Cambridge University Press
    • Bottou, L. (1998). Online algorithms and stochastic approximations. In D. Saad (Ed.), Online learning in neural networks. Cambridge: Cambridge University Press.
    • (1998) Online Learning in Neural Networks
    • Bottou, L.1
  • 6
    • 0030344230 scopus 로고    scopus 로고
    • Heuristics of instability and stabilization in model selection
    • Breiman, L. (1996). Heuristics of instability and stabilization in model selection. Annals of Statistics, 24, 2350-2383.
    • (1996) Annals of Statistics , vol.24 , pp. 2350-2383
    • Breiman, L.1
  • 7
    • 34250263445 scopus 로고
    • Smoothing noisy data with spline functions
    • Craven, P., & Wahba, G. (1979). Smoothing noisy data with spline functions. Numerical Mathematics, 31, 377-403.
    • (1979) Numerical Mathematics , vol.31 , pp. 377-403
    • Craven, P.1    Wahba, G.2
  • 8
    • 0004123838 scopus 로고    scopus 로고
    • Least absolute shrinkage is equivalent to quadratic penalization
    • L. Niklasson, M. Boden, & T. Ziemske (Eds.), Berlin: Springer-Verlag
    • Grandvalet, Y. (1998). Least absolute shrinkage is equivalent to quadratic penalization. In L. Niklasson, M. Boden, & T. Ziemske (Eds.), ICANN'98 (pp. 201-206). Berlin: Springer-Verlag.
    • (1998) ICANN'98 , pp. 201-206
    • Grandvalet, Y.1
  • 9
    • 0001704198 scopus 로고
    • Structural risk minimization for character recognition
    • J. Moody, S. Hanson, & R. Lipmann (Eds.), San Mateo, CA: Morgan Kaufmann
    • Guyon, I., Vapnik, V., Boser, B., Bottou, L., & Solla, S. A. (1992). Structural risk minimization for character recognition. In J. Moody, S. Hanson, & R. Lipmann (Eds.), Advances in neural information processing systems, 4 (pp. 471-479). San Mateo, CA: Morgan Kaufmann.
    • (1992) Advances in Neural Information Processing Systems , vol.4 , pp. 471-479
    • Guyon, I.1    Vapnik, V.2    Boser, B.3    Bottou, L.4    Solla, S.A.5
  • 10
    • 84977125093 scopus 로고
    • Learning translation invariant in massively parallel networks
    • J. de Bakker, A. Nijman, & P. Treleaven (Eds.), Berlin: Springer-Verlag
    • Hinton, G. (1987). Learning translation invariant in massively parallel networks. In J. de Bakker, A. Nijman, & P. Treleaven (Eds.), Proceedings of PARLE Conference on Parallel Architectures and Languages Europe (pp. 1-13). Berlin: Springer-Verlag.
    • (1987) Proceedings of PARLE Conference on Parallel Architectures and Languages Europe , pp. 1-13
    • Hinton, G.1
  • 11
    • 84942484786 scopus 로고
    • Ridge regression: Biased estimation for non-orthogonal problems
    • Hoerl, A., & Kennard, R. (1970). Ridge regression: Biased estimation for non-orthogonal problems. Technometrics, 12, 55-67.
    • (1970) Technometrics , vol.12 , pp. 55-67
    • Hoerl, A.1    Kennard, R.2
  • 12
    • 0008200145 scopus 로고    scopus 로고
    • Adaptive regularization in neural networks modeling
    • G. B. Orr & K.-R. Muller (Eds.), Berlin: Springer-Verlag
    • Larsen, J., Svarer, C., Andersen, L. N., & Hansen, L. K. (1998). Adaptive regularization in neural networks modeling. In G. B. Orr & K.-R. Muller (Eds.), Neural Networks: Tricks of the Trade (pp. 113-132). Berlin: Springer-Verlag.
    • (1998) Neural Networks: Tricks of the Trade , pp. 113-132
    • Larsen, J.1    Svarer, C.2    Andersen, L.N.3    Hansen, L.K.4
  • 15
    • 0001441372 scopus 로고
    • Probable networks and plausible predictions - A review of practical bayesian methods for supervised neural networks
    • MacKay D. (1995). Probable networks and plausible predictions - a review of practical Bayesian methods for supervised neural networks. Network: Computation in Neural Systems, 6, 469-505. Available online at: http://www.iro.umontreal.ca/~lisa.
    • (1995) Network: Computation in Neural Systems , vol.6 , pp. 469-505
    • Mackay, D.1
  • 16
    • 0001854616 scopus 로고    scopus 로고
    • Assessing relevance determination methods using delve
    • C. Bishop (Ed.), Berlin: Springer-Verlag
    • Neal, R. (1998). Assessing relevance determination methods using delve. In C. Bishop (Ed.), Neural networks and machine learning (pp. 97-129). Berlin: Springer-Verlag.
    • (1998) Neural Networks and Machine Learning , pp. 97-129
    • Neal, R.1
  • 17
    • 0022417790 scopus 로고
    • Computational vision and regularization theory
    • Poggio, T., Torre, V., & Koch, C. (1985). Computational vision and regularization theory. Nature, 317, 314-319.
    • (1985) Nature , vol.317 , pp. 314-319
    • Poggio, T.1    Torre, V.2    Koch, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.