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Regularization is a well studied problem in the context of neural networks.
Generalization and parameter estimation in feedforward nets: some experiments
Morgan, N. and Bourlard, H. (1990) · 1990
Earlier work this paper cites.
A simple weight decay can improve generalization
Krogh, A. and Hertz, J. A. (1991) · 1991
Earlier work this paper cites.
Nonparametric Regression and Generalized Linear Models
Green, Bernard W Silverman, B. W. S. (1993) · 1993
Earlier work this paper cites.
Training with noise is equivalent to Tikhonov regularization
Bishop, C. M. (1995) · 1995
Earlier work this paper cites.
The effects of adding noise during backpropagation training on a generalization performance
An, G. (1996) · 1996
Cited alongside, same era.
Gradient-based learning applied to document recognition
LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P. (1998) · 1998
Cited alongside, same era.
Calculation of the smoothing spline with weighted roughness measure
De Boor, C. (1998) · 2001
Cited alongside, same era.
Why does unsupervised pre-training help deep learning?
Erhan, D., Bengio, Y., Courville, A., Manzagol, P.-A., Vincent, P., and Bengio, S. (2010) · 2010
Later among the works it cites.
Deep sparse rectifier neural networks
Glorot, X., Bordes, A., and Bengio, Y. (2010) · 2010
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Rectified linear units improve restricted boltzmann machines
Nair, V. and Hinton, G. E. (2010) · 2010
Later among the works it cites.
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