| 2008 |
|---|
| 54 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
Decision Fusion on Boosting Ensembles.
ANNPR 2008: 157-167 |
| 53 | EE | Mercedes Fernández-Redondo,
Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa:
The Mixture of Neural Networks as Ensemble Combiner.
ANNPR 2008: 168-179 |
| 52 | EE | Carlos Hernández-Espinosa,
Joaquín Torres-Sospedra,
Mercedes Fernández-Redondo:
Researching on Multi-net Systems Based on Stacked Generalization.
ANNPR 2008: 193-204 |
| 51 | EE | 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 |
| 50 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
New Results on Combination Methods for Boosting Ensembles.
ICANN (1) 2008: 285-294 |
| 49 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
Researching on combining boosting ensembles.
IJCNN 2008: 2290-2295 |
| 2007 |
|---|
| 48 | EE | 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 |
| 47 | EE | 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 |
| 46 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
Mixing Aveboost and Conserboost to Improve Boosting Methods.
IJCNN 2007: 672-677 |
| 45 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
Designing a Multilayer Feedforward Ensemble with the Weighted Conservative Boosting Algorithm.
IJCNN 2007: 684-689 |
| 44 | EE | 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 |
|---|
| 43 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
Combining MF Networks: A Comparison Among Statistical Methods and Stacked Generalization.
ANNPR 2006: 210-220 |
| 42 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
An Experimental Study on Training Radial Basis Functions by Gradient Descent.
ANNPR 2006: 81-92 |
| 41 | EE | 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 |
| 40 | EE | Carlos Hernández-Espinosa,
Joaquín Torres-Sospedra,
Mercedes Fernández-Redondo:
Improving the Combination Module with a Neural Network.
ICIC (1) 2006: 146-155 |
| 39 | EE | Mercedes Fernández-Redondo,
Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa:
Gradient Descent and Radial Basis Functions.
ICIC (1) 2006: 391-396 |
| 38 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
Improving Adaptive Boosting with k-Cross-Fold Validation.
ICIC (1) 2006: 397-402 |
| 37 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
The Mixture of Neural Networks Adapted to Multilayer Feedforward Architecture.
ICIC (1) 2006: 488-493 |
| 36 | EE | 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 |
| 35 | EE | 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 |
| 34 | EE | 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 |
| 33 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
Designing a Multilayer Feedforward Ensembles with Cross Validated Boosting Algorithm.
IJCNN 2006: 1278-1283 |
| 32 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
Designing a New Multilayer Feedforward Modular Network for Classification Problems.
IJCNN 2006: 1284-1289 |
| 31 | EE | Mercedes Fernández-Redondo,
Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa:
Training Radial Basis Functions by Gradient Descent.
IJCNN 2006: 756-762 |
| 2005 |
|---|
| 30 | EE | Carlos Hernández-Espinosa,
Joaquín Torres-Sospedra,
Mercedes Fernández-Redondo:
Combination Methods for Ensembles of RBFs.
ICANN (2) 2005: 121-126 |
| 29 | EE | Joaquín Torres-Sospedra,
Mercedes Fernández-Redondo,
Carlos Hernández-Espinosa:
Combination Methods for Ensembles of MF.
ICANN (2) 2005: 133-138 |
| 28 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
New Results on Ensembles of Multilayer Feedforward.
ICANN (2) 2005: 139-144 |
| 27 | EE | Joaquín Torres-Sospedra,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
Ensembles of Multilayer Feedforward: Some New Results.
IWANN 2005: 604-611 |
| 2004 |
|---|
| 26 | EE | Mercedes Fernández-Redondo,
Carlos Hernández-Espinosa,
Mamen Ortiz-Gómez,
Joaquín Torres-Sospedra:
Training Radial Basis Functions by Gradient Descent.
ICAISC 2004: 184-189 |
| 25 | EE | Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo,
Joaquín Torres-Sospedra:
Experiments on Ensembles of Radial Basis Functions.
ICAISC 2004: 197-202 |
| 24 | EE | 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 |
| 23 | EE | Mercedes Fernández-Redondo,
Carlos Hernández-Espinosa,
Joaquín Torres-Sospedra:
Multilayer Feedforward Ensembles for Classification Problems.
ICONIP 2004: 744-749 |
| 22 | EE | Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo,
Joaquín Torres-Sospedra:
Ensembles of RBFs Trained by Gradient Descent.
ISNN (1) 2004: 223-228 |
| 21 | EE | Mercedes Fernández-Redondo,
Carlos Hernández-Espinosa,
Mamen Ortiz-Gómez,
Joaquín Torres-Sospedra:
Gradient Descent Training of Radial Basis Functions.
ISNN (1) 2004: 229-234 |
| 20 | EE | Mercedes Fernández-Redondo,
Carlos Hernández-Espinosa,
Joaquín Torres-Sospedra:
Classification by Multilayer Feedforward Ensembles.
ISNN (1) 2004: 852-857 |
| 19 | EE | 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 |
| 18 | EE | Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo,
Joaquín Torres-Sospedra:
Some Experiments on Ensembles of Neural Networks for Hyperspectral Image Classification.
KES 2004: 677-684 |
| 17 | EE | Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo,
Joaquín Torres-Sospedra:
First Experiments on Ensembles of Radial Basis Functions.
Multiple Classifier Systems 2004: 253-262 |
| 2003 |
|---|
| 16 | EE | Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo,
Mamen Ortiz-Gómez:
A new rule extraction algorithm based on interval arithmetic.
ESANN 2003: 155-160 |
| 15 | EE | Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo,
Mamen Ortiz-Gómez:
Ensemble Methods for Multilayer Feedforward.
ESANN 2003: 261-266 |
| 14 | EE | Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo,
Mamen Ortiz-Gómez:
Inversion of a Neural Network via Interval Arithmetic for Rule Extraction.
ICANN 2003: 670-677 |
| 13 | EE | 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 |
| 12 | EE | Mamen Ortiz-Gómez,
Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo:
An Empirical Comparison of Training Algorithms for Radial Basis Functions.
IWANN (2) 2003: 129-136 |
| 11 | EE | Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo,
Mamen Ortiz-Gómez:
Ensemble Methods for Multilayer Feedforward: An Experimental Study.
IWANN (2) 2003: 137-144 |
| 2001 |
|---|
| 10 | EE | Mercedes Fernández-Redondo,
Carlos Hernández-Espinosa:
Coding the outputs of multilayer feedforward.
ESANN 2001: 113-118 |
| 9 | EE | Mercedes Fernández-Redondo,
Carlos Hernández-Espinosa:
Weight initialization methods for multilayer feedforward.
ESANN 2001: 119-124 |
| 2000 |
|---|
| 8 | EE | Mercedes Fernández-Redondo,
Carlos Hernández-Espinosa:
Influence of weight-decay training in input selection methods.
ESANN 2000: 135-140 |
| 7 | EE | Mercedes Fernández-Redondo,
Carlos Hernández-Espinosa:
On the Combination of Weight-Decay and Input Selection Methods.
IJCNN (1) 2000: 191-196 |
| 6 | EE | Carlos Hernández-Espinosa,
Mercedes Fernández-Redondo,
Pedro Gómez Vilda:
Diagnosis of Vocal and Voice Disorders by the Speech Signal.
IJCNN (4) 2000: 253-258 |
| 5 | EE | Mercedes Fernández-Redondo,
Carlos Hernández-Espinosa:
A Comparison among Weight Initialization Methods for Multilayer Feedforward Networks.
IJCNN (4) 2000: 543-548 |
| 1999 |
|---|
| 4 | | 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 |
| 3 | | Mercedes Fernández-Redondo,
Carlos Hernández-Espinosa:
Optimal Use of a Trained Neural Network for Input Selection.
IWANN (2) 1999: 506-515 |
| 1998 |
|---|
| 2 | EE | Mercedes Fernández,
Carlos Hernández-Espinosa:
One or two hidden layers perceptrons.
ESANN 1998: 129-134 |
| 1 | EE | Mercedes Fernández,
Carlos Hernández-Espinosa:
On the error function of interval arithmetic backpropagation.
ESANN 1998: 135-140 |
