dblp.uni-trier.dewww.uni-trier.de

Mercedes Fernández-Redondo

List of publications from the DBLP Bibliography Server - FAQ
Coauthor Index - Ask others: ACM DL/Guide - CiteSeer - CSB - Google - MSN - Yahoo

2008
52EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Decision Fusion on Boosting Ensembles. ANNPR 2008: 157-167
51EEMercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa: The Mixture of Neural Networks as Ensemble Combiner. ANNPR 2008: 168-179
50EECarlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo: Researching on Multi-net Systems Based on Stacked Generalization. ANNPR 2008: 193-204
49EEJoaquín 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
48EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: New Results on Combination Methods for Boosting Ensembles. ICANN (1) 2008: 285-294
47EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Researching on combining boosting ensembles. IJCNN 2008: 2290-2295
2007
46EEJoaquín 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
45EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Stacking MF Networks to Combine the Outputs Provided by RBF Networks. ICANN (1) 2007: 450-459
44EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Mixing Aveboost and Conserboost to Improve Boosting Methods. IJCNN 2007: 672-677
43EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Designing a Multilayer Feedforward Ensemble with the Weighted Conservative Boosting Algorithm. IJCNN 2007: 684-689
42EEJoaquín 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
41EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Combining MF Networks: A Comparison Among Statistical Methods and Stacked Generalization. ANNPR 2006: 210-220
40EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: An Experimental Study on Training Radial Basis Functions by Gradient Descent. ANNPR 2006: 81-92
39EEMercedes 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
38EECarlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo: Improving the Combination Module with a Neural Network. ICIC (1) 2006: 146-155
37EEMercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa: Gradient Descent and Radial Basis Functions. ICIC (1) 2006: 391-396
36EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Improving Adaptive Boosting with k-Cross-Fold Validation. ICIC (1) 2006: 397-402
35EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: The Mixture of Neural Networks Adapted to Multilayer Feedforward Architecture. ICIC (1) 2006: 488-493
34EEMercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa: Training RBFs Networks: A Comparison Among Supervised and Not Supervised Algorithms. ICONIP (1) 2006: 477-486
33EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Mixture of Neural Networks: Some Experiments with the Multilayer Feedforward Architecture. ICONIP (1) 2006: 616-625
32EEJoaquín 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
31EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Designing a Multilayer Feedforward Ensembles with Cross Validated Boosting Algorithm. IJCNN 2006: 1278-1283
30EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Designing a New Multilayer Feedforward Modular Network for Classification Problems. IJCNN 2006: 1284-1289
29EEMercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa: Training Radial Basis Functions by Gradient Descent. IJCNN 2006: 756-762
2005
28EECarlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo: Combination Methods for Ensembles of RBFs. ICANN (2) 2005: 121-126
27EEJoaquín Torres-Sospedra, Mercedes Fernández-Redondo, Carlos Hernández-Espinosa: Combination Methods for Ensembles of MF. ICANN (2) 2005: 133-138
26EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: New Results on Ensembles of Multilayer Feedforward. ICANN (2) 2005: 139-144
25EEJoaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: Ensembles of Multilayer Feedforward: Some New Results. IWANN 2005: 604-611
2004
24EEMercedes Fernández-Redondo, Carlos Hernández-Espinosa, Mamen Ortiz-Gómez, Joaquín Torres-Sospedra: Training Radial Basis Functions by Gradient Descent. ICAISC 2004: 184-189
23EECarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra: Experiments on Ensembles of Radial Basis Functions. ICAISC 2004: 197-202
22EEMercedes 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
21EEMercedes Fernández-Redondo, Carlos Hernández-Espinosa, Joaquín Torres-Sospedra: Multilayer Feedforward Ensembles for Classification Problems. ICONIP 2004: 744-749
20EECarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra: Ensembles of RBFs Trained by Gradient Descent. ISNN (1) 2004: 223-228
19EEMercedes Fernández-Redondo, Carlos Hernández-Espinosa, Mamen Ortiz-Gómez, Joaquín Torres-Sospedra: Gradient Descent Training of Radial Basis Functions. ISNN (1) 2004: 229-234
18EEMercedes Fernández-Redondo, Carlos Hernández-Espinosa, Joaquín Torres-Sospedra: Classification by Multilayer Feedforward Ensembles. ISNN (1) 2004: 852-857
17EECarlos 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
16EECarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra: Some Experiments on Ensembles of Neural Networks for Hyperspectral Image Classification. KES 2004: 677-684
15EECarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Joaquín Torres-Sospedra: First Experiments on Ensembles of Radial Basis Functions. Multiple Classifier Systems 2004: 253-262
2003
14EECarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez: A new rule extraction algorithm based on interval arithmetic. ESANN 2003: 155-160
13EECarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez: Ensemble Methods for Multilayer Feedforward. ESANN 2003: 261-266
12EECarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez: Inversion of a Neural Network via Interval Arithmetic for Rule Extraction. ICANN 2003: 670-677
11EECarlos 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
10EEMamen Ortiz-Gómez, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo: An Empirical Comparison of Training Algorithms for Radial Basis Functions. IWANN (2) 2003: 129-136
9EECarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Mamen Ortiz-Gómez: Ensemble Methods for Multilayer Feedforward: An Experimental Study. IWANN (2) 2003: 137-144
2001
8EEMercedes Fernández-Redondo, Carlos Hernández-Espinosa: Coding the outputs of multilayer feedforward. ESANN 2001: 113-118
7EEMercedes Fernández-Redondo, Carlos Hernández-Espinosa: Weight initialization methods for multilayer feedforward. ESANN 2001: 119-124
2000
6EEMercedes Fernández-Redondo, Carlos Hernández-Espinosa: Influence of weight-decay training in input selection methods. ESANN 2000: 135-140
5EEMercedes Fernández-Redondo, Carlos Hernández-Espinosa: On the Combination of Weight-Decay and Input Selection Methods. IJCNN (1) 2000: 191-196
4EECarlos Hernández-Espinosa, Mercedes Fernández-Redondo, Pedro Gómez Vilda: Diagnosis of Vocal and Voice Disorders by the Speech Signal. IJCNN (4) 2000: 253-258
3EEMercedes Fernández-Redondo, Carlos Hernández-Espinosa: A Comparison among Weight Initialization Methods for Multilayer Feedforward Networks. IJCNN (4) 2000: 543-548
1999
2 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
1 Mercedes Fernández-Redondo, Carlos Hernández-Espinosa: Optimal Use of a Trained Neural Network for Input Selection. IWANN (2) 1999: 506-515

Coauthor Index

1Carlos Hernández-Espinosa [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52]
2Mamen Ortiz-Gómez [9] [10] [11] [12] [13] [14] [19] [22] [24]
3Joaquín Torres-Sospedra [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52]
4Pedro Gómez Vilda [4]

Copyright © Sun May 17 03:24:02 2009 by Michael Ley (ley@uni-trier.de)