S. Bakin, Adaptive Regression and Model Selection in Data Mining Problems, 1999.

L. Breiman, Heuristics of instability and stabilization in model selection. The Annals of Statistics, pp.2350-2383, 1996.

B. A. Brumback, D. Ruppert, M. P. Wand, T. S. Shively, R. Khon et al., Variable Selection and Function Estimation in Additive Nonparametric Regression Using a Data-Based Prior: Comment, Journal of the American Statistical Association, vol.94, issue.447, pp.94794-797, 1999.
DOI : 10.2307/2669991

E. Cantoni and T. J. Hastie, Degrees-of-freedom tests for smoothing splines, Biometrika, vol.89, issue.2, pp.251-263, 2002.
DOI : 10.1093/biomet/89.2.251

Z. Chen, Fitting multivariate regression functions by interaction spline models, J. R. Statist. Soc. B, vol.55, issue.2, pp.473-491, 1993.

Y. Grandvalet, Least Absolute Shrinkage is Equivalent to Quadratic Penalization, of Perspectives in Neural Computing, pp.201-206, 1998.
DOI : 10.1007/978-1-4471-1599-1_27

Y. Grandvalet and S. Canu, Outcomes of the equivalence of adaptive ridge with least absolute shrinkage, Advances in Neural Information Processing Systems 11, pp.445-451, 1998.

C. Gu and G. Wahba, Minimizing GCV/GML Scores with Multiple Smoothing Parameters via the Newton Method, SIAM Journal on Scientific and Statistical Computing, vol.12, issue.2, pp.383-398, 1991.
DOI : 10.1137/0912021

I. Guyon and A. Elisseeff, An introduction to variable and feature selection, Journal of Machine Learning Research, Special Issue on Variable/Feature Selection, vol.3, pp.1157-1182, 2003.

T. J. Hastie and R. J. Tibshirani, Generalized Additive Models, volume 43 of Monographs on Statistics and Applied Probability, 1990.

J. D. Opsomer and D. Ruppert, A Fully Automated Bandwidth Selection Method for Fitting Additive Models, Journal of the American Statistical Association, vol.22, issue.442, pp.166-179, 1998.
DOI : 10.1080/01621459.1995.10476630

M. R. Osborne, B. Presnell, and B. A. Turlach, On the lasso and its dual, Journal of Computational and Graphical Statistics, vol.9, issue.2, pp.319-337, 2000.

T. S. Shively, R. Khon, and S. Wood, Variable selection and function estimation in additive nonparametric regression using a data?based prior, Journal of the American Statistical Association, issue.447, pp.94777-806, 1999.

R. J. Tibshirani, Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society, B, vol.58, issue.1, pp.267-288, 1995.

R. J. Tibshirani and K. Knight, The Covariance Inflation Criterion for Adaptive Model Selection, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.61, issue.3, pp.61529-546, 1999.
DOI : 10.1111/1467-9868.00191

S. N. Wood, Modelling and smoothing parameter estimation with multiple quadratic penalties, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.62, issue.2, pp.413-428, 2000.
DOI : 10.1111/1467-9868.00240

J. Ye, On Measuring and Correcting the Effects of Data Mining and Model Selection, Journal of the American Statistical Association, vol.87, issue.441, pp.120-131, 1998.
DOI : 10.1080/01621459.1998.10474094