Ridge regression: applications to nonorthogonal problems, Technometrics, vol.12, issue.1, pp.69-82, 1970. ,
Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society, vol.58, issue.1, pp.267-288, 1996. ,
Sparse regression using mixed norms, Applied and Computational Harmonic Analysis, vol.27, issue.3, pp.303-324, 2009. ,
DOI : 10.1016/j.acha.2009.05.006
URL : https://hal.archives-ouvertes.fr/hal-00202904
Optmization with sparsity-inducing penalties, Machine Learning, pp.1-106, 2012. ,
Active set algorithm for structured sparsity-inducing norms, OPT 2009: 2nd NIPS Workshop on Optimization for Machine Learning, 2009. ,
Convex Optimization, 2004. ,
Compressible Distributions for Highdimensional Statistics, IEEE Transactions on Information Theory, 2012. ,
URL : https://hal.archives-ouvertes.fr/inria-00563207
Should Penalized Least Squares Regression be Interpreted as Maximum A Posteriori Estimation?, IEEE Transactions on Signal Processing, vol.59, issue.5, pp.2405-2410, 2011. ,
DOI : 10.1109/TSP.2011.2107908
URL : https://hal.archives-ouvertes.fr/inria-00486840
Efficiency of coordinate descent methods on huge-scale optimization problems. Core discussion papers, Center for Operations Research and Econometrics (CORE), 2010. ,
A dual coordinate descent method for large-scale linear SVM, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.408-415, 2008. ,
DOI : 10.1145/1390156.1390208
Stochastic low-rank kernel learning for regression, 28th International Conference on Machine Learning, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00657837
Learning to be bayesian without supervision, Adv. Neural Information Processing Systems (NIPS*06, 2007. ,
Reconciling " priors " & " priors " without prejudice? Research report RR-8366, 2013. ,