C De Mol

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Mario BerteroProfessor Emeritus, University of GenovaVerified email at unige.it
Michel DefriseDepartment Nuclear Medicine, Vrije Universiteit BrusselVerified email at vub.ac.be
Domenico GiannoneSenior Principal Economist, Amazon.comVerified email at amazon.com
Ingrid DaubechiesDuke UniversityVerified email at math.duke.edu
Lucrezia ReichlinProfessor of economics, London Business SchoolVerified email at london.edu
alessandro verriprofessor of computer science, dibris, università degli studi di genovaVerified email at unige.it
Francesca OdoneMaLGa Machine Learning Genoa Center - Università degli Studi di GenovaVerified email at unige.it
Ernesto De VitoMaLGa Machine Learning Genoa Center - Università di GenovaVerified email at unige.it
Lorenzo RosascoMaLGa Machine Learning Genoa Center - Università degli Studi di GenovaVerified email at mit.edu
Patrizia BoccacciAssociate Professor of Computer Science, Genoa University ItalyVerified email at disi.unige.it
Riccardo ZanellaInjeniaVerified email at injenia.it
Luca ZanniProfessor of Numerical Analysis, University of Modena and Reggio Emilia, Modena, ItalyVerified email at unimore.it
Massimo RobbertoSpace Telescope Science InstituteVerified email at stsci.edu
Eric GautierToulouse School of EconomicsVerified email at tse-fr.eu
Jeffrey M. WooldridgeUniversity Distinguished Professor of Economics, Michigan State UniversityVerified email at msu.edu
Herman Koene van DijkErasmus University, Tinbergen InstituteVerified email at ese.eur.nl
Dominique LesselierLaboratoire des Signaux et Systèmes UMR8506 (CNRS-CentraleSupélec-Université Paris-Sud), Université Paris-SaclayVerified email at l2s.centralesupelec.fr

C De Mol

Université Libre de Bruxelles

Verified email at ulb.ac.be


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
An iterative thresholding algorithm for linear inverse problems with a sparsity constraint I Daubechies, M Defrise, C De Mol Communications on Pure and Applied Mathematics, 2004	4933	2004
Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components? C De Mol, D Giannone, L Reichlin Journal of Econometrics 146 (2), 318-328, 2008	555	2008
Sparse and stable Markowitz portfolios J Brodie, I Daubechies, C De Mol, D Giannone, I Loris Proceedings of the National Academy of Sciences 106 (30), 12267-12272, 2009	467	2009
Linear inverse problems with discrete data. I. General formulation and singular system analysis M Bertero, C De Mol, ER Pike Inverse problems 1 (4), 301, 1985	366	1985
Linear inverse problems with discrete data: II. Stability and regularisation M Bertero, C De Mol, ER Pike Inverse problems 4 (3), 573, 1988	285	1988
Elastic-net regularization in learning theory C De Mol, E De Vito, L Rosasco Journal of Complexity 25 (2), 201-230, 2009	243	2009
The stability of inverse problems M Bertero, C De Mol, GA Viano Inverse scattering problems in optics, 161-214, 1980	149	1980
Generalised information theory for inverse problems in signal processing ER Pike, JG McWhirter, M Bertero, C De Mol IEE Proceedings F (Communications, Radar and Signal Processing) 131 (6), 660-667, 1984	100	1984
III Super-resolution by data inversion M Bertero, C De Mol Progress in optics 36, 129-178, 1996	92	1996
A regularized method for selecting nested groups of relevant genes from microarray data C De Mol, S Mosci, M Traskine, A Verri Journal of Computational Biology 16 (5), 677-690, 2009	87	2009
Resolution in diffraction-limited imaging, a singular value analysis M Bertero, P Brianzi, P Parker, ER Pike Optica Acta: International Journal of Optics 31 (2), 181-201, 1984	80	1984
Accelerating gradient projection methods for ℓ1-constrained signal recovery by steplength selection rules I Loris, M Bertero, C De Mol, R Zanella, L Zanni Applied and computational harmonic analysis 27 (2), 247-254, 2009	78	2009
Feature selection for high-dimensional data A Destrero, S Mosci, C De Mol, A Verri, F Odone Computational management science 6 (1), 25-40, 2009	72	2009
Regularized iterative and non-iterative procedures for object restoration from experimental data JB Abbiss, C De Mol, HS Dhadwal Optica Acta: International Journal of Optics 30 (1), 107-124, 1983	64	1983
A note on wavelet-based inversion algorithms C De Mol, M Defrise Contemporary Mathematics 313, 85-96, 2002	63	2002
Optimal combination of survey forecasts C Conflitti, C De Mol, D Giannone International Journal of Forecasting 31 (4), 1096-1103, 2015	57	2015
A regularized iterative algorithm for limited-angle inverse Radon transform M Defrise, C De Mol Optica Acta: International Journal of Optics 30 (4), 403-408, 1983	50	1983
A note on stopping rules for iterative regularisation methods and filtered SVD M Defrise, C De Mol Inverse Problems: An Interdisciplinary Study, 261-268, 1987	45	1987
Regularized iterative and noniterative procedures for object restoration in the presence of noise: an error analysis JB Abbiss, M Defrise, C De Mol, HS Dhadwal JOSA 73 (11), 1470-1475, 1983	43	1983
A sparsity-enforcing method for learning face features A Destrero, C De Mol, F Odone, A Verri IEEE Transactions on Image Processing 18 (1), 188-201, 2008	42	2008

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