

![0_image_0.png](0_image_0.png)

## Bibliography

An, G. (1996). The effects of adding noise during backpropagation training on a generalization performance. *Neural Comput.*, 8, 643–674.

Bishop, C. M. (1995). Training with noise is equivalent to Tikhonov regularization. *Neural* Computation, 7(1), 108–116.

De Boor, C. (1998). Calculation of the smoothing spline with weighted roughness measure. In Mathematical Models and Methods in Applied Sciences, page 2001.

Erhan, D., Bengio, Y., Courville, A., Manzagol, P.-A., Vincent, P., and Bengio, S. (2010). Why does unsupervised pre-training help deep learning? *JMLR*, 11, 625–660.

Glorot, X., Bordes, A., and Bengio, Y. (2010). Deep sparse rectifier neural networks. Deep Learning and Unsupervised Feature Learning Workshop - NIPS '10.

Green, Bernard W Silverman, B. W. S. (1993). Nonparametric Regression and Generalized Linear Models. CRC Press.

Krogh, A. and Hertz, J. A. (1991). A simple weight decay can improve generalization. In *NIPS*,
pages 950–957.

LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P. (1998). Gradient-based learning applied to document recognition. *Proceedings of the IEEE*, 86(11), 2278–2324.