A survey of methods for distributed machine learning D Peteiro-Barral, B Guijarro-Berdiñas Progress in Artificial Intelligence 2, 1-11, 2013 | 274 | 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 | 192 | 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 | 181 | 2006 |
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 | 131 | 2005 |
Online machine learning Ó Fontenla-Romero, B Guijarro-Berdiñas, D Martinez-Rego, ... Efficiency and scalability methods for computational intellect, 27-54, 2013 | 124 | 2013 |
A review of adaptive online learning for artificial neural networks B Pérez-Sánchez, O Fontenla-Romero, B Guijarro-Berdiñas Artificial Intelligence Review 49, 281-299, 2018 | 103 | 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 | 79 | 2002 |
Ingeniería del conocimiento: Aspectos metodológicos A Alonso Betanzos, B Guijarro Berdiñas, A Lozano Tello, ... Madrid: Pearson Prentice Hall,, 2004 | 71 | 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 | 67 | 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 | 63 | 2002 |
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 |
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 | 52 | 2013 |
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, 395-442, 2018 | 51 | 2018 |
A linear learning method for multilayer perceptrons using least-squares B Guijarro-Berdiñas, O Fontenla-Romero, B Pérez-Sánchez, P Fraguela Intelligent Data Engineering and Automated Learning-IDEAL 2007: 8th …, 2007 | 47 | 2007 |
A neural network approach for forestal fire risk estimation A Alonso-Betanzos, O Fontenla-Romero, B Guijarro-Berdinas, ... ECAI, 643-647, 2002 | 42 | 2002 |
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 | 39 | 2014 |
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 |
Large scale anomaly detection in mixed numerical and categorical input spaces C Eiras-Franco, D Martinez-Rego, B Guijarro-Berdinas, ... Information Sciences 487, 115-127, 2019 | 36 | 2019 |
A mixture of experts for classifying sleep apneas B Guijarro-Berdinas, E Hernandez-Pereira, D Peteiro-Barral Expert Systems with Applications 39 (8), 7084-7092, 2012 | 32 | 2012 |
Adaptive pattern recognition in the analysis of cardiotocographic records O Fontenla-Romero, A Alonso-Betanzos, B Guijarro-Berdiñas IEEE Transactions on Neural Networks 12 (5), 1188-1195, 2001 | 32 | 2001 |