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ORCIDMercedes Fernández-Redondo
Publications
- 2011
[c60]Joaquín Torres-Sospedra
, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Introducing Reordering Algorithms to Classic Well-Known Ensembles to Improve Their Performance. ICONIP (2) 2011: 572-579- [c59]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Improving Boosting Methods by Generating Specific Training and Validation Sets. ICONIP (2) 2011: 580-587 - [c58]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Using Bagging and Cross-Validation to Improve Ensembles Based on Penalty Terms. ICONIP (2) 2011: 588-595 - 2008
- [c57]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Decision Fusion on Boosting Ensembles. ANNPR 2008: 157-167 - [c56]Mercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa:
The Mixture of Neural Networks as Ensemble Combiner. ANNPR 2008: 168-179 - [c55]Carlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo:
Researching on Multi-net Systems Based on Stacked Generalization. ANNPR 2008: 193-204 - [c54]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Adding Diversity in Ensembles of Neural Networks by Reordering the Training Set. ICANN (1) 2008: 275-284 - [c53]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
New Results on Combination Methods for Boosting Ensembles. ICANN (1) 2008: 285-294 - [c52]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Researching on combining boosting ensembles. IJCNN 2008: 2290-2295 - 2007
- [c51]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Averaged Conservative Boosting: Introducing a New Method to Build Ensembles of Neural Networks. ICANN (1) 2007: 309-318 - [c50]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Stacking MF Networks to Combine the Outputs Provided by RBF Networks. ICANN (1) 2007: 450-459 - [c49]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Mixing Aveboost and Conserboost to Improve Boosting Methods. IJCNN 2007: 672-677 - [c48]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Designing a Multilayer Feedforward Ensemble with the Weighted Conservative Boosting Algorithm. IJCNN 2007: 684-689 - [c47]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Improving Adaptive Boosting with a Relaxed Equation to Update the Sampling Distribution. IWANN 2007: 119-126 - 2006
- [c46]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
An Experimental Study on Training Radial Basis Functions by Gradient Descent. ANNPR 2006: 81-92 - [c45]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Combining MF Networks: A Comparison Among Statistical Methods and Stacked Generalization. ANNPR 2006: 210-220 - [c44]Mercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa:
Improving the Expert Networks of a Modular Multi-Net System for Pattern Recognition. ICANN (1) 2006: 293-302 - [c43]Carlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo:
Improving the Combination Module with a Neural Network. ICIC (1) 2006: 146-155 - [c42]Mercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa:
Gradient Descent and Radial Basis Functions. ICIC (1) 2006: 391-396 - [c41]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Improving Adaptive Boosting with k-Cross-Fold Validation. ICIC (1) 2006: 397-402 - [c40]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
The Mixture of Neural Networks Adapted to Multilayer Feedforward Architecture. ICIC (1) 2006: 488-493 - [c39]Mercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa:
Training RBFs Networks: A Comparison Among Supervised and Not Supervised Algorithms. ICONIP (1) 2006: 477-486 - [c38]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Mixture of Neural Networks: Some Experiments with the Multilayer Feedforward Architecture. ICONIP (1) 2006: 616-625 - [c37]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Adaptive Boosting: Dividing the Learning Set to Increase the Diversity and Performance of the Ensemble. ICONIP (1) 2006: 688-697 - [c36]Mercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa:
Training Radial Basis Functions by Gradient Descent. IJCNN 2006: 756-762 - [c35]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Designing a Multilayer Feedforward Ensembles with Cross Validated Boosting Algorithm. IJCNN 2006: 1278-1283 - [c34]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Designing a New Multilayer Feedforward Modular Network for Classification Problems. IJCNN 2006: 1284-1289 - 2005
- [c33]Carlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo:
Combination Methods for Ensembles of RBFs. ICANN (2) 2005: 121-126 - [c32]Joaquín Torres-Sospedra, Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Combination Methods for Ensembles of MF. ICANN (2) 2005: 133-138 - [c31]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
New Results on Ensembles of Multilayer Feedforward. ICANN (2) 2005: 139-144 - [c30]Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
Ensembles of Multilayer Feedforward: Some New Results. IWANN 2005: 604-611 - 2004
- [c29]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa, Mamen Ortiz-Gómez, Joaquín Torres-Sospedra:
Training Radial Basis Functions by Gradient Descent. ICAISC 2004: 184-189 - [c28]Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra:
Experiments on Ensembles of Radial Basis Functions. ICAISC 2004: 197-202 - [c27]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa, Mamen Ortiz-Gómez, Joaquín Torres-Sospedra:
Some Experiments on Training Radial Basis Functions by Gradient Descent. ICONIP 2004: 428-433 - [c26]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa, Joaquín Torres-Sospedra:
Multilayer Feedforward Ensembles for Classification Problems. ICONIP 2004: 744-749 - [c25]Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra:
Ensembles of RBFs Trained by Gradient Descent. ISNN (1) 2004: 223-228 - [c24]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa, Mamen Ortiz-Gómez, Joaquín Torres-Sospedra:
Gradient Descent Training of Radial Basis Functions. ISNN (1) 2004: 229-234 - [c23]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa, Joaquín Torres-Sospedra:
Classification by Multilayer Feedforward Ensembles. ISNN (1) 2004: 852-857 - [c22]Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra:
Some Experiments with Ensembles of Neural Networks for Classification of Hyperspectral Images. ISNN (1) 2004: 912-917 - [c21]Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra:
Some Experiments on Ensembles of Neural Networks for Hyperspectral Image Classification. KES 2004: 677-684 - [c20]Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra:
First Experiments on Ensembles of Radial Basis Functions. Multiple Classifier Systems 2004: 253-262 - 2003
- [c19]Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez:
A new rule extraction algorithm based on interval arithmetic. ESANN 2003: 155-160 - [c18]Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez:
Ensemble Methods for Multilayer Feedforward. ESANN 2003: 261-266 - [c17]Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez:
Inversion of a Neural Network via Interval Arithmetic for Rule Extraction. ICANN 2003: 670-677 - [c16]Mamen Ortiz-Gómez, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
An Empirical Comparison of Training Algorithms for Radial Basis Functions. IWANN (2) 2003: 129-136 - [c15]Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez:
Ensemble Methods for Multilayer Feedforward: An Experimental Study. IWANN (2) 2003: 137-144 - [c14]Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez:
Rule Extraction from a Multilayer Feedforward Trained Network via Interval Arithmetic Inversion. IWANN (1) 2003: 622-630 - 2001
- [c13]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Coding the outputs of multilayer feedforward. ESANN 2001: 113-118 - [c12]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Weight initialization methods for multilayer feedforward. ESANN 2001: 119-124 - 2000
- [c11]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Influence of weight-decay training in input selection methods. ESANN 2000: 135-140 - [c10]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
On the Combination of Weight-Decay and Input Selection Methods. IJCNN (1) 2000: 191-196 - [c9]Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Pedro Gómez Vilda:
Diagnosis of Vocal and Voice Disorders by the Speech Signal. IJCNN (4) 2000: 253-258 - [c8]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
A Comparison among Weight Initialization Methods for Multilayer Feedforward Networks. IJCNN (4) 2000: 543-548 - 1999
- [c7]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Neural networks input selection by using the training set. IJCNN 1999: 1189-1194 - [c6]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
A comparison between two interval arithmetic learning algorithms. IJCNN 1999: 1293-1297 - [c5]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Input selection by multilayer feedforward trained networks. IJCNN 1999: 1834-1839 - [c4]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Generalization capability of one and two hidden layers. IJCNN 1999: 1840-1843 - [c3]Juan Ignacio Godino-Llorente, Santiago Aguilera-Navarro, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo, Pedro Gómez Vilda:
On the selection of meaningful speech parameters used by a pathologic/non pathologic voice register classifier. EUROSPEECH 1999: 563-566 - [c2]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
How to Select the Inputs for a Multilayer Feedforward Network by Using the Training Set. IWANN (2) 1999: 477-486 - [c1]Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Optimal Use of a Trained Neural Network for Input Selection. IWANN (2) 1999: 506-515
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last updated on 2024-04-25 01:56 CEST by the dblp team
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