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Volumn 38, Issue , 2015, Pages 192-204

The loss surfaces of multilayer networks

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; HAMILTONIANS; RANDOM VARIABLES; SIMULATED ANNEALING; SPIN GLASS;

EID: 84954310140     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper
Times cited : (860)

References (25)
  • 1
    • 11744358706 scopus 로고
    • Spin-glass models of neural networks
    • [Amit et al., 1985]
    • [Amit et al., 1985] Amit, D. J., Gutfreund, H., and Sompolinsky, H. (1985). Spin-glass models of neural networks. Phys. Rev. A, 32:1007-1018.
    • (1985) Phys. Rev. A , vol.32 , pp. 1007-1018
    • Amit, D.J.1    Gutfreund, H.2    Sompolinsky, H.3
  • 4
    • 0024774330 scopus 로고
    • Neural networks and principal component analysis: Learning from examples without local minima
    • [Baldi and Hornik, 1989]
    • [Baldi and Hornik, 1989] Baldi, P. and Hornik, K. (1989). Neural networks and principal component analysis: Learning from examples without local minima. Neural Networks, 2:53-58.
    • (1989) Neural Networks , vol.2 , pp. 53-58
    • Baldi, P.1    Hornik, K.2
  • 5
    • 0013309537 scopus 로고    scopus 로고
    • Online algorithms and stochastic approximations
    • [Bottou, 1998]. Cambridge University Press
    • [Bottou, 1998] Bottou, L. (1998). Online algorithms and stochastic approximations. In Online Learning and Neural Networks. Cambridge University Press.
    • (1998) Online Learning and Neural Networks
    • Bottou, L.1
  • 6
    • 34147142335 scopus 로고    scopus 로고
    • The statistics of critical points of Gaussian fields on large-dimensional spaces
    • [Bray and Dean, 2007]
    • [Bray and Dean, 2007] Bray, A. J. and Dean, D. S. (2007). The statistics of critical points of Gaussian fields on large-dimensional spaces. Physics Review Letter.
    • (2007) Physics Review Letter
    • Bray, A.J.1    Dean, D.S.2
  • 7
    • 84928534967 scopus 로고    scopus 로고
    • Identifying and attacking the saddle point problem in high-dimensional non-convex optimization
    • [Dauphin et al., 2014]
    • [Dauphin et al., 2014] Dauphin, Y., Pascanu, R., Giilcehre, CC., Cho, K., Ganguli, S., and Bengio, Y. (2014). Identifying and attacking the saddle point problem in high-dimensional non-convex optimization. In NIPS.
    • (2014) NIPS
    • Dauphin, Y.1    Pascanu, R.2    Giilcehre, C.C.3    Cho, K.4    Ganguli, S.5    Bengio, Y.6
  • 9
    • 84898971588 scopus 로고    scopus 로고
    • Predicting parameters in deep learning
    • [Denil et al., 2013]
    • [Denil et al., 2013] Denil, M., Shakibi, B., Dinh, L., Ranzato, M., and Freitas, N. D. (2013). Predicting parameters in deep learning. In NIPS.
    • (2013) NIPS
    • Denil, M.1    Shakibi, B.2    Dinh, L.3    Ranzato, M.4    Freitas, N.D.5
  • 10
    • 84937896655 scopus 로고    scopus 로고
    • Exploiting linear structure within convolutional networks for efficient evaluation
    • [Denton et al., 2014]
    • [Denton et al., 2014] Denton, E., Zaremba, W., Bruna, J., LeCun, Y., and Fergus, R. (2014). Exploiting linear structure within convolutional networks for efficient evaluation. In NIPS.
    • (2014) NIPS
    • Denton, E.1    Zaremba, W.2    Bruna, J.3    LeCun, Y.4    Fergus, R.5
  • 12
    • 36448994342 scopus 로고    scopus 로고
    • Replica symmetry breaking condition exposed by random matrix calculation of landscape complexity
    • [Fyodorov and Williams, 2007]
    • [Fyodorov and Williams, 2007] Fyodorov, Y. V. and Williams, I. (2007). Replica symmetry breaking condition exposed by random matrix calculation of landscape complexity. Journal ofStatistical Physics, 129(5-6), 1081-1116.
    • (2007) Journal OfStatistical Physics , vol.129 , Issue.5-6 , pp. 1081-1116
    • Fyodorov, Y.V.1    Williams, I.2
  • 16
    • 84876231242 scopus 로고    scopus 로고
    • Imagenet classification with deep convolutional neural networks
    • [Krizhevsky et al., 2012]
    • [Krizhevsky et al., 2012] Krizhevsky, A., Sutskever, I., and Hinton, G. (2012). Imagenet classification with deep convolutional neural networks. In NIPS.
    • (2012) NIPS
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.3
  • 17
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • [LeCun et al., 1998a]
    • [LeCun et al., 1998a] LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P. (1998a). Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86:2278-2324.
    • (1998) Proceedings of the IEEE , vol.86 , pp. 2278-2324
    • LeCun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 19
    • 77956509090 scopus 로고    scopus 로고
    • Rectified linear units improve restricted boltzmann machines
    • [Nair and Hinton, 2010]
    • [Nair and Hinton, 2010] Nair, V. and Hinton, G. (2010). Rectified linear units improve restricted boltzmann machines. In ICML.
    • (2010) ICML
    • Nair, V.1    Hinton, G.2
  • 20
    • 0031558831 scopus 로고    scopus 로고
    • Mean-field theory for a spin-glass model of neural networks: Tap free energy and the paramagnetic to spin-glass transition
    • [Nakanishi and Takayama, 1997]
    • [Nakanishi and Takayama, 1997] Nakanishi, K. and Takayama, H. (1997). Mean-field theory for a spin-glass model of neural networks: Tap free energy and the paramagnetic to spin-glass transition. Journal of Physics A: Mathematical and General, 30:8085.
    • (1997) Journal of Physics A: Mathematical and General , vol.30 , pp. 8085
    • Nakanishi, K.1    Takayama, H.2
  • 21
  • 22
    • 4243050152 scopus 로고
    • Exact solution for on-line learning in multilayer neural networks
    • [Saad and Solla, 1995]
    • [Saad and Solla, 1995] Saad, D. and Solla, S. A. (1995). Exact solution for on-line learning in multilayer neural networks. Physical Review Letters, 74(21):4337.
    • (1995) Physical Review Letters , vol.74 , Issue.21 , pp. 4337
    • Saad, D.1    Solla, S.A.2
  • 23
    • 85083950783 scopus 로고    scopus 로고
    • Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
    • [Saxe et al., 2014]
    • [Saxe et al., 2014] Saxe, A. M., McClelland, J. L., and Ganguli, S. (2014). Exact solutions to the nonlinear dynamics of learning in deep linear neural networks. In ICLR.
    • (2014) ICLR
    • Saxe, A.M.1    McClelland, J.L.2    Ganguli, S.3
  • 24
    • 84926060006 scopus 로고    scopus 로고
    • Tagspace: Semantic embed-dings from hashtags
    • [Weston et al., 2014]
    • [Weston et al., 2014] Weston, J., Chopra, S., and Adams, K. (2014). #tagspace: Semantic embed-dings from hashtags. In EMNLP.
    • (2014) EMNLP
    • Weston, J.1    Chopra, S.2    Adams, K.3
  • 25
    • 0001560594 scopus 로고
    • On the distribution of the roots of certain symmetric matrices
    • [Wigner, 1958]
    • [Wigner, 1958] Wigner, E. P. (1958). On the Distribution of the Roots of Certain Symmetric Matrices. The Annals of Mathematics, 67:325-327.
    • (1958) The Annals of Mathematics , vol.67 , pp. 325-327
    • Wigner, E.P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.