| 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 57 (11), 1413-1457, 2004 | 5935 | 2004 |
| Introduction to inverse problems in imaging M Bertero, P Boccacci, C De Mol CRC press, 2021 | 3194 | 2021 |
| 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 | 619 | 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 | 608 | 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 | 384 | 1985 |
| Elastic-net regularization in learning theory C De Mol, E De Vito, L Rosasco Journal of Complexity 25 (2), 201-230, 2009 | 346 | 2009 |
| Linear inverse problems with discrete data: II. Stability and regularisation M Bertero, C De Mol, ER Pike Inverse problems 4 (3), 573, 1988 | 298 | 1988 |
| The stability of inverse problems M Bertero, C De Mol, GA Viano Inverse scattering problems in optics, 161-214, 1980 | 163 | 1980 |
| III Super-resolution by data inversion M Bertero, C De Mol Progress in optics 36, 129-178, 1996 | 107 | 1996 |
| 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 | 103 | 1984 |
| Optimal combination of survey forecasts C Conflitti, C De Mol, D Giannone International Journal of Forecasting 31 (4), 1096-1103, 2015 | 95 | 2015 |
| 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 | 86 | 2009 |
| Feature selection for high-dimensional data A Destrero, S Mosci, C De Mol, A Verri, F Odone Computational management science 6, 25-40, 2009 | 86 | 2009 |
| 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 | 80 | 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 | 69 | 1983 |
| A note on wavelet-based inversion algorithms C De Mol, M Defrise Contemporary Mathematics 313, 85-96, 2002 | 66 | 2002 |
| Inverse scattering problems in optics M Bertero, C De Mol, GA Viano Topics in current physics 20, 161-214, 1980 | 61 | 1980 |
| 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 | 54 | 1987 |
| 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 | 54 | 1983 |
| Super-resolution in confocal scanning microscopy: II. The incoherent case M Bertero, P Boccacci, M Defrise, C De Mol, ER Pike Inverse Problems 5 (4), 441, 1989 | 45 | 1989 |
Mario BerteroProfessor Emeritus, University of Genova在 unige.it 的电子邮件经过验证
