Bertha Guijarro-Berdiñas
Bertha Guijarro-Berdiñas
Bestätigte E-Mail-Adresse bei UDC.ES
Zitiert von
Zitiert von
A survey of methods for distributed machine learning
D Peteiro-Barral, B Guijarro-Berdiñas
Progress in Artificial Intelligence 2, 1-11, 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
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
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
Online machine learning
Ó Fontenla-Romero, B Guijarro-Berdiñas, D Martinez-Rego, ...
Efficiency and Scalability Methods for Computational Intellect, 27-54, 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
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
Ingeniería del conocimiento: Aspectos metodológicos
A Alonso Betanzos, B Guijarro Berdiñas, A Lozano Tello, ...
Madrid: Pearson Prentice Hall,, 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
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
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 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
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
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
A neural network approach for forestal fire risk estimation
A Alonso-Betanzos, O Fontenla-Romero, B Guijarro-Berdinas, ...
ECAI, 643-647, 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
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
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
The PATRICIA project: A semantic-based methodology for intelligent monitoring in the ICU
V Moret-Bonillo, A Alonso-Betanzos, E Garcia-Martin, M Cabrero-Canosa, ...
IEEE Engineering in Medicine and Biology Magazine 12 (4), 59-68, 1993
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
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