| A survey of methods for distributed machine learning D Peteiro-Barral, B Guijarro-Berdiñas Progress in Artificial Intelligence 2 (1), 1-11, 2013 | 300 | 2013 |
| An intelligent system for forest fire risk prediction and fire fighting management in Galicia A Alonso-Betanzos, O Fontenla-Romero, B Guijarro-Berdiñas, ... Expert systems with applications 25 (4), 545-554, 2003 | 214 | 2003 |
| A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis. E Castillo, B Guijarro-Berdinas, O Fontenla-Romero, A Alonso-Betanzos, ... Journal of Machine Learning Research 7 (7), 2006 | 184 | 2006 |
| Online machine learning Ó Fontenla-Romero, B Guijarro-Berdiñas, D Martinez-Rego, ... Efficiency and scalability methods for computational intellect, 27-54, 2013 | 139 | 2013 |
| A new method for sleep apnea classification using wavelets and feedforward neural networks O Fontenla-Romero, B Guijarro-Berdinas, A Alonso-Betanzos, ... Artificial Intelligence in Medicine 34 (1), 65-76, 2005 | 129 | 2005 |
| A review of adaptive online learning for artificial neural networks B Pérez-Sánchez, O Fontenla-Romero, B Guijarro-Berdiñas Artificial Intelligence Review 49 (2), 281-299, 2018 | 119 | 2018 |
| A global optimum approach for one-layer neural networks E Castillo, O Fontenla-Romero, B Guijarro-Berdinas, A Alonso-Betanzos Neural Computation 14 (6), 1429-1449, 2002 | 81 | 2002 |
| Ingeniería del conocimiento: Aspectos metodológicos A Alonso Betanzos, B Guijarro Berdiñas, A Lozano Tello, ... Madrid: Pearson Prentice Hall,, 2004 | 72 | 2004 |
| Distributed one-class support vector machine E Castillo, D Peteiro-Barral, BG Berdiñas, O Fontenla-Romero International journal of neural systems 25 (07), 1550029, 2015 | 70 | 2015 |
| Intelligent analysis and pattern recognition in cardiotocographic signals using a tightly coupled hybrid system B Guijarro-Berdiñas, A Alonso-Betanzos, O Fontenla-Romero Artificial Intelligence 136 (1), 1-27, 2002 | 66 | 2002 |
| On the scalability of feature selection methods on high-dimensional data V Bolón-Canedo, D Rego-Fernández, D Peteiro-Barral, ... Knowledge and Information Systems 56 (2), 395-442, 2018 | 62 | 2018 |
| A methodology for improving tear film lipid layer classification B Remeseiro, V Bolon-Canedo, D Peteiro-Barral, A Alonso-Betanzos, ... IEEE journal of biomedical and health informatics 18 (4), 1485-1493, 2013 | 60 | 2013 |
| A new convex objective function for the supervised learning of single-layer neural networks O Fontenla-Romero, B Guijarro-Berdiñas, B Pérez-Sánchez, ... Pattern Recognition 43 (5), 1984-1992, 2010 | 54 | 2010 |
| Adaptive inverse control using an online learning algorithm for neural networks JL Calvo-Rolle, O Fontenla-Romero, B Pérez-Sánchez, ... Informatica 25 (3), 401-414, 2014 | 45 | 2014 |
| A linear learning method for multilayer perceptrons using least-squares B Guijarro-Berdiñas, O Fontenla-Romero, B Pérez-Sánchez, P Fraguela International Conference on Intelligent Data Engineering and Automated …, 2007 | 45 | 2007 |
| Large scale anomaly detection in mixed numerical and categorical input spaces C Eiras-Franco, D Martinez-Rego, B Guijarro-Berdiñas, ... Information Sciences 487, 115-127, 2019 | 42 | 2019 |
| A neural network approach for forestal fire risk estimation A Alonso-Betanzos, O Fontenla-Romero, B Guijarro-Berdinas, ... ECAI, 643-647, 2002 | 42 | 2002 |
| The NST-EXPERT project: the need to evolve A Alonso-Betanzos, B Guijarro-Berdiñas, V Moret-Bonillo, ... Artificial Intelligence in Medicine 7 (4), 297-313, 1995 | 38 | 1995 |
| Fast deep autoencoder for federated learning D Novoa-Paradela, O Fontenla-Romero, B Guijarro-Berdiñas Pattern Recognition 143, 109805, 2023 | 35 | 2023 |
| Scalable feature selection using ReliefF aided by locality‐sensitive hashing C Eiras‐Franco, B Guijarro‐Berdiñas, A Alonso‐Betanzos, A Bahamonde International Journal of Intelligent Systems 36 (11), 6161-6179, 2021 | 35 | 2021 |
