Oscar Fontenla-Romero
Oscar Fontenla-Romero
Associate Professor of Computer Science. University of A Coruña (Spain)
Verified email at udc.es
TitleCited byYear
A very fast learning method for neural networks based on sensitivity analysis
E Castillo, B Guijarro-Berdiñas, O Fontenla-Romero, A Alonso-Betanzos
Journal of Machine Learning Research 7 (Jul), 1159-1182, 2006
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
Automatic bearing fault diagnosis based on one-class ν-SVM
D FernáNdez-Francos, D MartíNez-Rego, O Fontenla-Romero, ...
Computers & Industrial Engineering 64 (1), 357-365, 2013
A new method for sleep apnea classification using wavelets and feedforward neural networks
O Fontenla-Romero, B Guijarro-Berdiñas, A Alonso-Betanzos, ...
Artificial Intelligence in Medicine 34 (1), 65-76, 2005
A global optimum approach for one-layer neural networks
E Castillo, O Fontenla-Romero, B Guijarro-Berdiñas, A Alonso-Betanzos
Neural Computation 14 (6), 1429-1449, 2002
Linear-least-squares initialization of multilayer perceptrons through backpropagation of the desired response
D Erdogmus, O Fontenla-Romero, JC Principe, A Alonso-Betanzos, ...
IEEE Transactions on Neural Networks 16 (2), 325-337, 2005
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
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
Conversion methods for symbolic features: A comparison applied to an intrusion detection problem
E Hernández-Pereira, JA Suárez-Romero, O Fontenla-Romero, ...
Expert Systems with Applications 36 (7), 10612-10617, 2009
Multispectral classification of grass weeds and wheat (Triticum durum) using linear and nonparametric functional discriminant analysis and neural networks
Weed Research 48 (1), 28-37, 2008
A robust incremental learning method for non-stationary environments
D Martínez-Rego, B Pérez-Sánchez, O Fontenla-Romero, ...
Neurocomputing 74 (11), 1800-1808, 2011
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
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
Online machine learning
Ó Fontenla-Romero, B Guijarro-Berdiñas, D Martinez-Rego, ...
Efficiency and Scalability Methods for Computational Intellect, 27-54, 2013
Power wind mill fault detection via one-class ν-SVM vibration signal analysis
D Martinez-Rego, O Fontenla-Romero, A Alonso-Betanzos
The 2011 International Joint Conference on Neural Networks, 511-518, 2011
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
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
Efficiency of local models ensembles for time series prediction
D Martínez-Rego, O Fontenla-Romero, A Alonso-Betanzos
Expert Systems with Applications 38 (6), 6884-6894, 2011
Accelerating the convergence speed of neural networks learning methods using least squares.
O Fontenla-Romero, D Erdogmus, JC Príncipe, A Alonso-Betanzos, ...
ESANN, 255-260, 2003
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
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Articles 1–20