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The weight-decay technique in learning from data: an optimization point of view

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  • Giorgio Gnecco
  • Marcello Sanguineti

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Suggested Citation

  • Giorgio Gnecco & Marcello Sanguineti, 2009. "The weight-decay technique in learning from data: an optimization point of view," Computational Management Science, Springer, vol. 6(1), pages 53-79, February.
    • Handle: RePEc:spr:comgts:v:6:y:2009:i:1:p:53-79
    DOI: 10.1007/s10287-008-0072-5
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    References listed on IDEAS

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    1. Amit Gupta & Monica Lam, 1998. "The weight decay backpropagation for generalizations with missing values," Annals of Operations Research, Springer, vol. 78(0), pages 165-187, January.
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    Cited by:

    1. L.-F. Pau, 2014. "Discovering the dynamics of smart business networks," Computational Management Science, Springer, vol. 11(4), pages 445-458, October.
    2. Hong Seok Park & Dinh Son Nguyen & Thai Le-Hong & Xuan Tran, 2022. "Machine learning-based optimization of process parameters in selective laser melting for biomedical applications," Journal of Intelligent Manufacturing, Springer, vol. 33(6), pages 1843-1858, August.

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