Mercedes Fernández-Redondo

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Viewing Publication 1 - 61 from 61

2011

Using Bagging and Cross-Validation to Improve Ensembles Based on Penalty TermsJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. iconip 2011: 588-595 [doi]

Introducing Reordering Algorithms to Classic Well-Known Ensembles to Improve Their PerformanceJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. iconip 2011: 572-579 [doi]

Improving Boosting Methods by Generating Specific Training and Validation SetsJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. iconip 2011: 580-587 [doi]

2008

The Mixture of Neural Networks as Ensemble CombinerMercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa. annpr 2008: 168-179 [doi]

Researching on Multi-net Systems Based on Stacked GeneralizationCarlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo. annpr 2008: 193-204 [doi]

Adding Diversity in Ensembles of Neural Networks by Reordering the Training SetJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. icann 2008: 275-284 [doi]

Researching on combining boosting ensemblesJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. ijcnn 2008: 2290-2295 [doi]

New Results on Combination Methods for Boosting EnsemblesJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. icann 2008: 285-294 [doi]

Decision Fusion on Boosting EnsemblesJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. annpr 2008: 157-167 [doi]

2007

Improving Adaptive Boosting with a Relaxed Equation to Update the Sampling DistributionJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. iwann 2007: 119-126 [doi]

Mixing Aveboost and Conserboost to Improve Boosting MethodsJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. ijcnn 2007: 672-677 [doi]

Averaged Conservative Boosting: Introducing a New Method to Build Ensembles of Neural NetworksJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. icann 2007: 309-318 [doi]

Stacking MF Networks to Combine the Outputs Provided by RBF NetworksJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. icann 2007: 450-459 [doi]

Designing a Multilayer Feedforward Ensemble with the Weighted Conservative Boosting AlgorithmJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. ijcnn 2007: 684-689 [doi]

2006

Training Radial Basis Functions by Gradient DescentMercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa. ijcnn 2006: 756-762 [doi]

Training RBFs Networks: A Comparison Among Supervised and Not Supervised AlgorithmsMercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa. iconip 2006: 477-486 [doi]

Improving the Expert Networks of a Modular Multi-Net System for Pattern RecognitionMercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa. icann 2006: 293-302 [doi]

Gradient Descent and Radial Basis FunctionsMercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa. icic 2006: 391-396 [doi]

Improving the Combination Module with a Neural NetworkCarlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo. icic 2006: 146-155 [doi]

Designing a Multilayer Feedforward Ensembles with Cross Validated Boosting AlgorithmJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. ijcnn 2006: 1278-1283 [doi]

An Experimental Study on Training Radial Basis Functions by Gradient DescentJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. annpr 2006: 81-92 [doi]

Mixture of Neural Networks: Some Experiments with the Multilayer Feedforward ArchitectureJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. iconip 2006: 616-625 [doi]

Adaptive Boosting: Dividing the Learning Set to Increase the Diversity and Performance of the EnsembleJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. iconip 2006: 688-697 [doi]

Improving Adaptive Boosting with ::::k::::-Cross-Fold ValidationJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. icic 2006: 397-402 [doi]

Designing a New Multilayer Feedforward Modular Network for Classification ProblemsJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. ijcnn 2006: 1284-1289 [doi]

The Mixture of Neural Networks Adapted to Multilayer Feedforward ArchitectureJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. icic 2006: 488-493 [doi]

Combining MF Networks: A Comparison Among Statistical Methods and Stacked GeneralizationJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. annpr 2006: 210-220 [doi]

2005

2004

Some Experiments on Training Radial Basis Functions by Gradient DescentMercedes Fernández-Redondo, Carlos Hernández-Espinosa, Mamen Ortiz-Gómez, Joaquín Torres-Sospedra. iconip 2004: 428-433 [doi]

Classification by Multilayer Feedforward EnsemblesMercedes Fernández-Redondo, Carlos Hernández-Espinosa, Joaquín Torres-Sospedra. isnn 2004: 852-857 [doi]

Multilayer Feedforward Ensembles for Classification ProblemsMercedes Fernández-Redondo, Carlos Hernández-Espinosa, Joaquín Torres-Sospedra. iconip 2004: 744-749 [doi]

Gradient Descent Training of Radial Basis FunctionsMercedes Fernández-Redondo, Carlos Hernández-Espinosa, Mamen Ortiz-Gómez, Joaquín Torres-Sospedra. isnn 2004: 229-234 [doi]

Training Radial Basis Functions by Gradient DescentMercedes Fernández-Redondo, Carlos Hernández-Espinosa, Mamen Ortiz-Gómez, Joaquín Torres-Sospedra. icaisc 2004: 184-189 [doi]

Some Experiments on Ensembles of Neural Networks for Hyperspectral Image ClassificationCarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra. kes 2004: 677-684 [doi]

Ensembles of RBFs Trained by Gradient DescentCarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra. isnn 2004: 223-228 [doi]

First Experiments on Ensembles of Radial Basis FunctionsCarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra. mcs 2004: 253-262 [doi]

Experiments on Ensembles of Radial Basis FunctionsCarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra. icaisc 2004: 197-202 [doi]

Some Experiments with Ensembles of Neural Networks for Classification of Hyperspectral ImagesCarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra. isnn 2004: 912-917 [doi]

2003

Ensemble Methods for Multilayer Feedforward: An Experimental StudyCarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez. iwann 2003: 137-144 [doi]

Ensemble Methods for Multilayer FeedforwardCarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez. esann 2003: 261-266 [doi]

Inversion of a Neural Network via Interval Arithmetic for Rule ExtractionCarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez. icann 2003: 670-677 [doi]

A new rule extraction algorithm based on interval arithmeticCarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez. esann 2003: 155-160 [doi]

Rule Extraction from a Multilayer Feedforward Trained Network via Interval Arithmetic InversionCarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez. iwann 2003: 622-630 [doi]

An Empirical Comparison of Training Algorithms for Radial Basis FunctionsMamen Ortiz-Gómez, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo. iwann 2003: 129-136 [doi]

2001

Coding the outputs of multilayer feedforwardMercedes Fernández-Redondo, Carlos Hernández-Espinosa. esann 2001: 113-118 [doi]

Weight initialization methods for multilayer feedforwardMercedes Fernández-Redondo, Carlos Hernández-Espinosa. esann 2001: 119-124 [doi]

Hacia un diseño óptimo de la arquitectura Multilayer FeedforwardMercedes Fernández-Redondo. PhD thesis, Jaume I University, Spain, 2001. [doi]

2000

1999

Optimal Use of a Trained Neural Network for Input SelectionMercedes Fernández-Redondo, Carlos Hernández-Espinosa. iwann 1999: 506-515

How to Select the Inputs for a Multilayer Feedforward Network by Using the Training SetMercedes Fernández-Redondo, Carlos Hernández-Espinosa. iwann 1999: 477-486

Input selection by multilayer feedforward trained networksMercedes Fernández-Redondo, Carlos Hernández-Espinosa. ijcnn 1999: 1834-1839 [doi]

A comparison between two interval arithmetic learning algorithmsMercedes Fernández-Redondo, Carlos Hernández-Espinosa. ijcnn 1999: 1293-1297 [doi]

Generalization capability of one and two hidden layersMercedes Fernández-Redondo, Carlos Hernández-Espinosa. ijcnn 1999: 1840-1843 [doi]

Neural networks input selection by using the training setMercedes Fernández-Redondo, Carlos Hernández-Espinosa. ijcnn 1999: 1189-1194 [doi]

On the selection of meaningful speech parameters used by a pathologic/non pathologic voice register classifierJuan Ignacio Godino-Llorente, Santiago Aguilera-Navarro, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Pedro Gómez Vilda. interspeech 1999: 563-566 [doi]

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1999

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