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
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
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
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 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
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
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
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
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
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