Combining geometry and combinatorics: A unified approach to sparse signal recovery, 2008 46th Annual Allerton Conference on Communication, Control, and Computing, pp.798-805, 2008. ,
DOI : 10.1109/ALLERTON.2008.4797639
Simultaneous analysis of lasso and dantzig selector. The Annals of Statistics, pp.1705-1732, 2009. ,
URL : https://hal.archives-ouvertes.fr/hal-00401585
Statistics for high-dimensional data, 2011. ,
DOI : 10.1007/978-3-642-20192-9
Near-ideal model selection by â ? D¸S1D¸S1 minimization . The Annals of Statistics, pp.2145-2177, 2009. ,
Stable signal recovery from incomplete and inaccurate measurements, Communications on Pure and Applied Mathematics, vol.7, issue.8, pp.591207-1223, 2006. ,
DOI : 10.1002/cpa.20124
Interactions between compressed sensing, random matrices, and high dimensional geometry. to appear in "Panoramas et Synthèses, p.2013 ,
A remark on the lasso and the Dantzig selector, Statistics & Probability Letters, vol.83, issue.1, 2012. ,
DOI : 10.1016/j.spl.2012.09.020
URL : https://hal.archives-ouvertes.fr/hal-00678421
Optimal designs for lasso and dantzig selector using expander codes Arxiv preprint arXiv, 1010. ,
Least angle regression . The Annals of statistics, pp.407-499, 2004. ,
On sparse representations in arbitrary redundant bases. Information Theory, IEEE Transactions on, vol.50, issue.6, pp.1341-1344, 2004. ,
Statistical inference for sobol pick freeze monte carlo method. arXiv preprint arXiv:1303, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00804668
Toeplitz and Circulant Matrices: A Review, Foundations and Trends?? in Communications and Information Theory, vol.2, issue.3, 2002. ,
DOI : 10.1561/0100000006
Probability Inequalities for Sums of Bounded Random Variables, Journal of the American Statistical Association, vol.1, issue.301, pp.13-30, 1963. ,
DOI : 10.1214/aoms/1177730491
Asymptotic normality and efficiency of two Sobol index estimators, ESAIM: Probability and Statistics, vol.18, 2012. ,
DOI : 10.1051/ps/2013040
URL : https://hal.archives-ouvertes.fr/hal-00665048
Estimating mean dimensionality, 2003. ,
Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators, Electronic Journal of Statistics, vol.2, issue.0, pp.90-102, 2008. ,
DOI : 10.1214/08-EJS177
URL : https://hal.archives-ouvertes.fr/hal-00222251
Uncertainty and sensitivity analysis for crop models, Working with Dynamic Crop Models: Evaluation, Analysis, Parameterization, and Applications, pp.55-99, 2006. ,
Factorial Sampling Plans for Preliminary Computational Experiments, Technometrics, vol.1, issue.2, pp.161-174, 1991. ,
DOI : 10.2307/1266468
Global sensitivity analysis: the primer, 2008. ,
DOI : 10.1002/9780470725184
Sensitivity estimates for nonlinear mathematical models, Math. Modeling Comput. Experiment, vol.1, issue.4, pp.407-414, 1993. ,
Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates, Mathematics and Computers in Simulation, vol.55, issue.1-3, pp.271-280, 2001. ,
DOI : 10.1016/S0378-4754(00)00270-6
Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society. Series B (Methodological), pp.267-288, 1996. ,
Bias correction for the estimation of sensitivity indices based on random balance designs, Reliability Engineering & System Safety, vol.107, pp.205-213, 2012. ,
DOI : 10.1016/j.ress.2012.06.010
URL : https://hal.archives-ouvertes.fr/hal-00507526
Estimating sobol'indices combining monte carlo estimators and latin hypercube sampling, 2012. ,
Just relax: Convex programming methods for identifying sparse signals in noise. Information Theory, IEEE Transactions on, vol.52, issue.3, pp.1030-1051, 2006. ,
Lower bounds on the maximum cross correlation of signals (corresp.) Information Theory, IEEE Transactions on, vol.20, issue.3, pp.397-399, 1974. ,
Further Results on Performance Analysis for Compressive Sensing Using Expander Graphs, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers, pp.621-625, 2007. ,
DOI : 10.1109/ACSSC.2007.4487288
On model selection consistency of lasso, The Journal of Machine Learning Research, vol.7, pp.2541-2563, 2006. ,