	Rakotomamonjy, A. and Bach, F. and Canu, S. and Grandvalet, Y.	Bibtex
SimpleMKL		[pdf]
Journal of Machine Learning Research, vol. 9, pp. 2491-2521, 2008
	Rakotomamonjy, A. and Bach, F.R. and Canu, S. and Grandvalet, Y.	Bibtex
More Efficiency in Multiple Kernel Learning		[pdf]
Proceedings of the 24th Annual International Conference on Machine Learning (ICML 2007), ed.: Ghahramani Z., pp. 775-782, 2007
	Szafranski, M. and Grandvalet, Y. and Rakotomamonjy, A.	Bibtex
Composite Kernel Learning		[pdf]
International Conference on Machine Learning (ICML 2008), pp. 1040-1047, july, 2008
	Szafranski, M. and Grandvalet, Y. and Morizet-Mahoudeaux, P.	Bibtex
Hierarchical Penalization		[pdf]
Advances in Neural Information Processing Systems 20 (NIPS 2007), pp. 1457-1464, MIT press, 2008
	Avalos, M. and Grandvalet, Y. and Ambroise, C.	Bibtex
Parsimonious Additive Models		[pdf]
Computational Statistics and Data Analysis, vol. 51, num. 6, pp. 2851-2870, 2007
	Grandvalet, Y. and Canu, S.	Bibtex
Adaptive Scaling for Feature Selection in SVMs		[pdf]
Advances in Neural Information Processing Systems 15 (NIPS 2002), pp. 569-576, MIT press, 2003		[ps.gz]
	Grandvalet, Y. and Canu, S.	Bibtex
Outcomes of the equivalence of adaptive ridge with least absolute shrinkage		[pdf]
Advances in Neural Information Processing Systems 11 (NIPS 1998), pp. 445-451, MIT press, 1999		[ps.gz]
	Grandvalet, Y.	Bibtex
Least absolute shrinkage is equivalent to quadratic penalization		[pdf]
ICANN'98, Perspectives in Neural Computing, pp. 201-206, Springer, 1998		[ps.gz]
	Matlab function for doing adaptive ridge regression or lasso	Matlab code