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Regularization and statistical learning theory for data analysis

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  • Evgeniou, Theodoros
  • Poggio, Tomaso
  • Pontil, Massimiliano
  • Verri, Alessandro

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Suggested Citation

  • Evgeniou, Theodoros & Poggio, Tomaso & Pontil, Massimiliano & Verri, Alessandro, 2002. "Regularization and statistical learning theory for data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 421-432, February.
    • Handle: RePEc:eee:csdana:v:38:y:2002:i:4:p:421-432
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    Cited by:

    1. Ana Suárez-Vázquez & José Quevedo, 2015. "Analyzing superstars’ power using support vector machines," Empirical Economics, Springer, vol. 49(4), pages 1521-1542, December.
    2. Shiyi Chen & Kiho Jeong & Wolfgang K. Härdle, 2008. "Recurrent Support Vector Regression for a Nonlinear ARMA Model with Applications to Forecasting Financial Returns," SFB 649 Discussion Papers SFB649DP2008-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Shiyi Chen & Kiho Jeong & Wolfgang Härdle, 2015. "Recurrent support vector regression for a non-linear ARMA model with applications to forecasting financial returns," Computational Statistics, Springer, vol. 30(3), pages 821-843, September.
    4. Sachin Kumar & T. Gopi & N. Harikeerthana & Munish Kumar Gupta & Vidit Gaur & Grzegorz M. Krolczyk & ChuanSong Wu, 2023. "Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control," Journal of Intelligent Manufacturing, Springer, vol. 34(1), pages 21-55, January.

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