| Neural fraud detection in credit card operations JR Dorronsoro, F Ginel, C Sgnchez, CS Cruz IEEE transactions on neural networks 8 (4), 827-834, 1997 | 389 | 1997 |
| Regression tree ensembles for wind energy and solar radiation prediction A Torres-Barrán, Á Alonso, JR Dorronsoro Neurocomputing 326, 151-160, 2019 | 259 | 2019 |
| Hybrid machine learning forecasting of solar radiation values Y Gala, Á Fernández, J Díaz, JR Dorronsoro Neurocomputing 176, 48-59, 2016 | 150 | 2016 |
| Finding optimal model parameters by discrete grid search ÁB Jiménez, JL Lázaro, JR Dorronsoro Innovations in hybrid intelligent systems, 120-127, 2008 | 124 | 2008 |
| A characterization of potential spaces JR Dorronsoro Proceedings of the American Mathematical Society 95 (1), 21-31, 1985 | 107 | 1985 |
| Deep neural networks for wind and solar energy prediction D Díaz–Vico, A Torres–Barrán, A Omari, JR Dorronsoro Neural Processing Letters 46 (3), 829-844, 2017 | 95 | 2017 |
| Supervised outlier detection for classification and regression Á Fernández, J Bella, JR Dorronsoro Neurocomputing 486, 77-92, 2022 | 69 | 2022 |
| Group fused lasso CM Alaíz, A Barbero, JR Dorronsoro International Conference on Artificial Neural Networks, 66-73, 2013 | 60 | 2013 |
| Finding optimal model parameters by deterministic and annealed focused grid search ÁB Jiménez, JL Lázaro, JR Dorronsoro Neurocomputing 72 (13-15), 2824-2832, 2009 | 58 | 2009 |
| Combining numerical weather predictions and satellite data for PV energy nowcasting A Catalina, CM Alaiz, JR Dorronsoro IEEE Transactions on Sustainable Energy 11 (3), 1930-1937, 2019 | 55 | 2019 |
| Optimal tuning of a networked linear controller using a multi-objective genetic algorithm. Application to a complex electromechanical process D Martin, B Caballero, R Haber Innovative Computing, Information and Control, International Conference on …, 2008 | 55 | 2008 |
| Mean oscillation and Besov spaces JR Dorronsoro Canadian Mathematical Bulletin 28 (4), 474-480, 1985 | 49 | 1985 |
| Differentiability properties of functions with bounded variation JR Dorronsoro Indiana University Mathematics Journal, 1027-1045, 1989 | 48 | 1989 |
| Simple proof of convergence of the SMO algorithm for different SVM variants J Lopez, JR Dorronsoro IEEE Transactions on Neural Networks and Learning Systems 23 (7), 1142-1147, 2012 | 45 | 2012 |
| Deep least squares Fisher discriminant analysis D Diaz-Vico, JR Dorronsoro IEEE transactions on neural networks and learning systems 31 (8), 2752-2763, 2019 | 41 | 2019 |
| Sparse LS-SVMs with L0–norm minimization J Lopez, K De Brabanter, JR Dorronsoro, JAK Suykens Proceedings of the European symposium on artificial neural networks …, 2011 | 36 | 2011 |
| On the equivalence of the SMO and MDM algorithms for SVM training J López, Á Barbero, JR Dorronsoro Joint European Conference on Machine Learning and Knowledge Discovery in …, 2008 | 35 | 2008 |
| A nonlinear discriminant algorithm for feature extraction and data classification C Santa Cruz, JR Dorronsoro IEEE transactions on neural networks 9 (6), 1370-1376, 1998 | 35* | 1998 |
| Deep support vector neural networks D Diaz-Vico, J Prada, A Omari, J Dorronsoro Integrated Computer-Aided Engineering 27 (4), 389-402, 2020 | 32 | 2020 |
| Day-ahead price forecasting for the spanish electricity market J Díaz, Á Romero, JR Dorronsoro International Journal of Interactive Multimedia and Artificial Intelligence …, 2019 | 32 | 2019 |
