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2020 – today
- 2023
[j82]Javier Mediavilla-Relaño
, Marcelino Lázaro, Aníbal R. Figueiras-Vidal:
Imbalance example-dependent cost classification: A Bayesian based method. Expert Syst. Appl. 213(Part): 118909 (2023)- [j81]Aitor Gutiérrez-López, Francisco Javier González-Serrano, Aníbal R. Figueiras-Vidal:
Optimum Bayesian thresholds for rebalanced classification problems using class-switching ensembles. Pattern Recognit. 135: 109158 (2023) - [j80]Marcelino Lázaro, Aníbal R. Figueiras-Vidal:
Neural network for ordinal classification of imbalanced data by minimizing a Bayesian cost. Pattern Recognit. 137: 109303 (2023) - 2022
- [c73]María-Elena Fernández-García, Antonio Ros-Ros, Eloy Hontoria Hernández, Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez:
Double-Layer Stacked Denoising Autoencoders for Regression. IWINAC (1) 2022: 337-345 - 2021
- [j79]Alexander Benítez-Buenache, Lorena Álvarez-Pérez, Aníbal R. Figueiras-Vidal:
On the design of Bayesian principled algorithms for imbalanced classification. Knowl. Based Syst. 221: 106969 (2021) - [j78]Adrián Sánchez-Morales, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Complete autoencoders for classification with missing values. Neural Comput. Appl. 33(6): 1951-1957 (2021) - [j77]María-Elena Fernández-García, José-Luis Sancho-Gómez, Antonio Ros-Ros, Aníbal R. Figueiras-Vidal:
Complete Stacked Denoising Auto-Encoders for Regression. Neural Process. Lett. 53(1): 787-797 (2021) - [j76]Marcelino Lázaro, Aníbal R. Figueiras-Vidal:
A Bayes Risk Minimization Machine for Example-Dependent Cost Classification. IEEE Trans. Cybern. 51(7): 3524-3534 (2021) - 2020
- [j75]Alexander Benítez-Buenache, Lorena Álvarez-Pérez, V. John Mathews, Aníbal R. Figueiras-Vidal:
Corrigendum to "Likelihood ratio equivalence and imbalanced binary classification" [Expert Systems with Applications, Volume 130 (2019), Pages 84-96]. Expert Syst. Appl. 146: 113299 (2020) - [j74]Juan-Antonio Martínez-García, José-Luis Sancho-Gómez, Adrián Sánchez-Morales, Aníbal R. Figueiras-Vidal:
Designing non-linear minimax and related discriminants by disjoint tangent configurations applied to RBF networks. Neurocomputing 383: 106-112 (2020) - [j73]Aitor Gutiérrez-López, Francisco Javier González-Serrano, Aníbal R. Figueiras-Vidal:
Asymmetric label switching resists binary imbalance. Inf. Fusion 60: 20-24 (2020) - [j72]Siham Tabik, Ricardo F. Alvear-Sandoval, María M. Ruiz, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Francisco Herrera:
MNIST-NET10: A heterogeneous deep networks fusion based on the degree of certainty to reach 0.1% error rate. Ensembles overview and proposal. Inf. Fusion 62: 73-80 (2020) - [j71]Marcelino Lázaro, Francisco Herrera, Aníbal R. Figueiras-Vidal:
Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification. Inf. Sci. 520: 31-45 (2020) - [j70]Adrián Sánchez-Morales, José-Luis Sancho-Gómez, Juan-Antonio Martínez-García, Aníbal R. Figueiras-Vidal:
Improving deep learning performance with missing values via deletion and compensation. Neural Comput. Appl. 32(17): 13233-13244 (2020) - [i1]Siham Tabik, Ricardo F. Alvear-Sandoval, María M. Ruiz, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Francisco Herrera:
A tutorial on ensembles and deep learning fusion with MNIST as guiding thread: A complex heterogeneous fusion scheme reaching 10 digits error. CoRR abs/2001.11486 (2020)
2010 – 2019
- 2019
- [j69]Alexander Benítez-Buenache, Lorena Álvarez-Pérez, V. John Mathews, Aníbal R. Figueiras-Vidal:
Likelihood ratio equivalence and imbalanced binary classification. Expert Syst. Appl. 130: 84-96 (2019) - [j68]Adrián Sánchez-Morales, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Exploiting label information to improve auto-encoding based classifiers. Neurocomputing 370: 104-108 (2019) - [j67]Ricardo F. Alvear-Sandoval, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
On improving CNNs performance: The case of MNIST. Inf. Fusion 52: 106-109 (2019) - [c72]Javier Mediavilla-Relaño, Aitor Gutiérrez-López, Marcelino Lázaro, Aníbal R. Figueiras-Vidal:
A Principled Two-Step Method for Example-Dependent Cost Binary Classification. IWINAC (2) 2019: 13-22 - [c71]María-Elena Fernández-García, Jorge Larrey-Ruiz, Antonio Ros-Ros, Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez:
Machine-Health Application Based on Machine Learning Techniques for Prediction of Valve Wear in a Manufacturing Plant. IWINAC (2) 2019: 389-398 - 2018
- [j66]José-Luis Sancho-Gómez, Juan-Antonio Martínez-García, Stanley C. Ahalt, Aníbal R. Figueiras-Vidal:
Linear discriminants described by disjoint tangent configurations. Neurocomputing 316: 345-356 (2018) - [j65]Ricardo F. Alvear-Sandoval, Aníbal R. Figueiras-Vidal:
On building ensembles of stacked denoising auto-encoding classifiers and their further improvement. Inf. Fusion 39: 41-52 (2018) - [j64]Ricardo F. Alvear-Sandoval, Aníbal R. Figueiras-Vidal:
On building ensembles of stacked denoising auto-encoding classifiers and their further improvement - a correction. Inf. Fusion 40: 126 (2018) - [j63]Marcelino Lázaro, Monson H. Hayes, Aníbal R. Figueiras-Vidal:
Training neural network classifiers through Bayes risk minimization applying unidimensional Parzen windows. Pattern Recognit. 77: 204-215 (2018) - [c70]David Díaz-Vico, Aníbal R. Figueiras-Vidal, José R. Dorronsoro:
Deep MLPs for Imbalanced Classification. IJCNN 2018: 1-7 - 2017
- [j62]Sergio González, Salvador García, Marcelino Lázaro, Aníbal R. Figueiras-Vidal, Francisco Herrera:
Class Switching according to Nearest Enemy Distance for learning from highly imbalanced data-sets. Pattern Recognit. 70: 12-24 (2017) - [j61]Anas Ahachad, Lorena Álvarez-Pérez, Aníbal R. Figueiras-Vidal:
Boosting ensembles with controlled emphasis intensity. Pattern Recognit. Lett. 88: 1-5 (2017) - [c69]Francisco Javier González-Serrano, Aníbal R. Figueiras-Vidal:
Generalized CMAC adaptive ensembles for concept-drifting data streams. EUSIPCO 2017: 2669-2673 - [c68]Lorena Álvarez-Pérez, Anas Ahachad, Aníbal R. Figueiras-Vidal:
Pre-emphasizing Binarized Ensembles to Improve Classification Performance. IWANN (1) 2017: 339-350 - [c67]Adrián Sánchez-Morales, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Values Deletion to Improve Deep Imputation Processes. IWINAC (2) 2017: 240-246 - 2016
- [j60]Luis Munoz-Gonzalez, Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal:
Laplace Approximation for Divisive Gaussian Processes for Nonstationary Regression. IEEE Trans. Pattern Anal. Mach. Intell. 38(3): 618-624 (2016) - [c66]Ricardo F. Alvear-Sandoval, Aníbal R. Figueiras-Vidal:
An Experiment in Pre-Emphasizing Diversified Deep Neural Classifiers. ESANN 2016 - [c65]Manuel Montoya-Catala, Ricardo F. Alvear-Sandoval, Aníbal R. Figueiras-Vidal:
Experiments in combining boosting and deep stacked networks. MLSP 2016: 1-6 - 2015
- [j59]Efraín Mayhua-López, Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal:
A new boosting design of Support Vector Machine classifiers. Inf. Fusion 25: 63-71 (2015) - [j58]Adil Omari, Aníbal R. Figueiras-Vidal:
Post-aggregation of classifier ensembles. Inf. Fusion 26: 96-102 (2015) - [j57]Anas Ahachad, Adil Omari, Aníbal R. Figueiras-Vidal:
Neighborhood Guided Smoothed Emphasis for Real Adaboost Ensembles. Neural Process. Lett. 42(1): 155-165 (2015) - [c64]Marcelino Lázaro, Francisco Herrera, Aníbal R. Figueiras-Vidal:
Classification of Binary Imbalanced Data Using A Bayesian Ensemble of Bayesian Neural Networks. EANN 2015: 304-314 - [c63]R. F. Alvear-Sandoval, Aníbal R. Figueiras-Vidal:
Does diversity improve deep learning? EUSIPCO 2015: 2496-2500 - 2014
- [j56]Luis Munoz-Gonzalez, Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal:
Divisive Gaussian Processes for Nonstationary Regression. IEEE Trans. Neural Networks Learn. Syst. 25(11): 1991-2003 (2014) - [c62]Luis Munoz-Gonzalez, Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal:
Laplace approximation with Gaussian Processes for volatility forecasting. CIP 2014: 1-6 - 2013
- [j55]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Classifying patterns with missing values using Multi-Task Learning perceptrons. Expert Syst. Appl. 40(4): 1333-1341 (2013) - [j54]Adil Omari, Aníbal R. Figueiras-Vidal:
Feature Combiners With Gate-Generated Weights for Classification. IEEE Trans. Neural Networks Learn. Syst. 24(1): 158-163 (2013) - [j53]Luis Antonio Azpicueta-Ruiz, Marcus Zeller, Aníbal R. Figueiras-Vidal, Walter Kellermann, Jerónimo Arenas-García:
Enhanced Adaptive Volterra Filtering by Automatic Attenuation of Memory Regions and Its Application to Acoustic Echo Cancellation. IEEE Trans. Signal Process. 61(11): 2745-2750 (2013) - [c61]Anas Ahachad, Adil Omari, Aníbal R. Figueiras-Vidal:
Smoothed Emphasis for Boosting Ensembles. IWANN (1) 2013: 367-375 - 2012
- [j52]Efraín Mayhua-López, Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal:
Real AdaBoost With Gate Controlled Fusion. IEEE Trans. Neural Networks Learn. Syst. 23(12): 2003-2009 (2012) - [c60]Aníbal R. Figueiras-Vidal, Lior Rokach:
An Exploration of Research Directions in Machine Ensemble Theory and Applications. ESANN 2012 - 2011
- [j51]Luis Antonio Azpicueta-Ruiz, Marcus Zeller, Aníbal R. Figueiras-Vidal, Jerónimo Arenas-García, Walter Kellermann:
Adaptive Combination of Volterra Kernels and Its Application to Nonlinear Acoustic Echo Cancellation. IEEE Trans. Speech Audio Process. 19(1): 97-110 (2011) - [c59]Luis Antonio Azpicueta-Ruiz, Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal, Jerónimo Arenas-García:
A block-based approach to adaptively bias the weights of adaptive filters. MLSP 2011: 1-6 - [c58]Luis Munoz-Gonzalez, Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal:
Heteroscedastic Gaussian process regression using expectation propagation. MLSP 2011: 1-6 - 2010
- [j50]Vanessa Gómez-Verdejo, Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal:
Committees of Adaboost ensembles with modified emphasis functions. Neurocomputing 73(7-9): 1289-1292 (2010) - [j49]Miguel Lázaro-Gredilla, Joaquin Quiñonero Candela, Carl Edward Rasmussen, Aníbal R. Figueiras-Vidal:
Sparse Spectrum Gaussian Process Regression. J. Mach. Learn. Res. 11: 1865-1881 (2010) - [j48]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Pattern classification with missing data: a review. Neural Comput. Appl. 19(2): 263-282 (2010) - [j47]Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal:
Marginalized neural network mixtures for large-scale regression. IEEE Trans. Neural Networks 21(8): 1345-1351 (2010) - [j46]Miguel Lázaro-Gredilla, Luis Antonio Azpicueta-Ruiz, Aníbal R. Figueiras-Vidal, Jerónimo Arenas-García:
Adaptively biasing the weights of adaptive filters. IEEE Trans. Signal Process. 58(7): 3890-3895 (2010) - [c57]Soufiane El Jelali, Abdelouahid Lyhyaoui, Aníbal R. Figueiras-Vidal:
A pseudoregression formulation of emphasized soft target procedures for classification problems. ESANN 2010 - [c56]Efraín Mayhua-López, Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal:
Improving boosting performance with a local combination of learners. IJCNN 2010: 1-7 - [c55]Luis Antonio Azpicueta-Ruiz, Marcus Zeller, Aníbal R. Figueiras-Vidal, Jerónimo Arenas-García:
Least-squares adaptation of affine combinations of multiple adaptive filters. ISCAS 2010: 2976-2979
2000 – 2009
- 2009
- [j45]Soufiane El Jelali, Abdelouahid Lyhyaoui, Aníbal R. Figueiras-Vidal:
Designing Model Based Classifiers by Emphasizing Soft Targets. Fundam. Informaticae 96(4): 419-433 (2009) - [j44]José-Luis Sancho-Gómez, Pedro J. García-Laencina, Aníbal R. Figueiras-Vidal:
Combining Missing Data Imputation and Pattern Classification in a Multi-Layer Perceptron. Intell. Autom. Soft Comput. 15(4): 539-553 (2009) - [j43]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Michel Verleysen:
K nearest neighbours with mutual information for simultaneous classification and missing data imputation. Neurocomputing 72(7-9): 1483-1493 (2009) - [j42]I. Mora-Jiménez, Aníbal R. Figueiras-Vidal:
Improving performance of neural classifiers via selective reduction of target levels. Neurocomputing 72(13-15): 3020-3027 (2009) - [j41]Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal:
Adaptive Combination of Proportionate Filters for Sparse Echo Cancellation. IEEE Trans. Speech Audio Process. 17(6): 1087-1098 (2009) - [c54]Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal:
Inter-domain Gaussian Processes for Sparse Inference using Inducing Features. NIPS 2009: 1087-1095 - 2008
- [j40]Theodoros Evgeniou, Aníbal R. Figueiras-Vidal, Sergios Theodoridis:
Emerging Machine Learning Techniques in Signal Processing. EURASIP J. Adv. Signal Process. 2008 (2008) - [j39]José Luis Rojo-Álvarez, Manel Martínez-Ramón, Jordi Muñoz-Marí, Gustavo Camps-Valls, Carlos M. Cruz, Aníbal R. Figueiras-Vidal:
Sparse Deconvolution Using Support Vector Machines. EURASIP J. Adv. Signal Process. 2008 (2008) - [j38]Vanessa Gómez-Verdejo, Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal:
A Dynamically Adjusted Mixed Emphasis Method for Building Boosting Ensembles. IEEE Trans. Neural Networks 19(1): 3-17 (2008) - [c53]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal, Michel Verleysen:
K-nearest neighbours based on mutual information for incomplete data classification. ESANN 2008: 37-42 - [c52]Soufiane El Jelali, Abdelouahid Lyhyaoui, Aníbal R. Figueiras-Vidal:
An emphasized target smoothing procedure to improve MLP classifiers performance. ESANN 2008: 499-504 - [c51]Luis Antonio Azpicueta-Ruiz, Aníbal R. Figueiras-Vidal, Jerónimo Arenas-García:
A normalized adaptation scheme for the convex combination of two adaptive filters. ICASSP 2008: 3301-3304 - [c50]Soufiane El Jelali, Abdelouahid Lyhyaoui, Aníbal R. Figueiras-Vidal:
Applying emphasized soft targets for Gaussian Mixture Model based classification. IMCSIT 2008: 131-136 - 2007
- [j37]Jerónimo Arenas-García, Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal:
Fast evaluation of neural networks via confidence rating. Neurocomputing 70(16-18): 2775-2782 (2007) - [c49]Marcelino Lázaro, José M. Leiva-Murillo, Antonio Artés-Rodríguez, Aníbal R. Figueiras-Vidal:
A New Cost Function for Binary Classification Problems Based on the Distributions of the Soft Output for Each Class. IJCNN 2007: 1464-1469 - [c48]Jaisiel Madrid-Sánchez, Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal:
A Single Layer Perceptron Approach to Selective Multi-task Learning. IWINAC (1) 2007: 272-281 - [c47]Pedro J. García-Laencina, Jesús Serrano-García, Aníbal R. Figueiras-Vidal, José-Luis Sancho-Gómez:
Multi-task Neural Networks for Dealing with Missing Inputs. IWINAC (1) 2007: 282-291 - 2006
- [j36]Vanessa Gómez-Verdejo, Manuel Ortega-Moral, Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal:
Boosting by weighting critical and erroneous samples. Neurocomputing 69(7-9): 679-685 (2006) - [j35]Jerónimo Arenas-García, Manel Martínez-Ramón, Ángel Navia-Vázquez, Aníbal R. Figueiras-Vidal:
Plant identification via adaptive combination of transversal filters. Signal Process. 86(9): 2430-2438 (2006) - [j34]Manel Martínez-Ramón, José Luis Rojo-Álvarez, Gustavo Camps-Valls, Jordi Muñoz-Marí, Ángel Navia-Vázquez, Emilio Soria-Olivas, Aníbal R. Figueiras-Vidal:
Support Vector Machines for Nonlinear Kernel ARMA System Identification. IEEE Trans. Neural Networks 17(6): 1617-1622 (2006) - [j33]Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal, Ali H. Sayed:
Mean-square performance of a convex combination of two adaptive filters. IEEE Trans. Signal Process. 54(3): 1078-1090 (2006) - [c46]Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal:
Designing neural network committees by combining boosting ensembles. ESANN 2006: 419-424 - [c45]Miguel Lázaro-Gredilla, Jaisiel Madrid-Sánchez, Aníbal R. Figueiras-Vidal:
A new cost function to build MLPs by means of regularized boosting. Computational Intelligence 2006: 162-167 - [c44]Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal:
Improved Blind Equalization via Adaptive Combination of Constant Modulus Algorithms. ICASSP (3) 2006: 756-759 - [c43]Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal:
Pattern Classification with Missing Values using Multitask Learning. IJCNN 2006: 3594-3601 - 2005
- [j32]José Luis Rojo-Álvarez, Gustavo Camps-Valls, Manel Martínez-Ramón, Emilio Soria-Olivas, Ángel Navia-Vázquez, Aníbal R. Figueiras-Vidal:
Support vector machines framework for linear signal processing. Signal Process. 85(12): 2316-2326 (2005) - [j31]Jerónimo Arenas-García, Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal:
New algorithms for improved adaptive convex combination of LMS transversal filters. IEEE Trans. Instrum. Meas. 54(6): 2239-2249 (2005) - [c42]Vanessa Gómez-Verdejo, Manuel Ortega-Moral, Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal:
Boosting by weighting boundary and erroneous samples. ESANN 2005: 85-90 - [c41]Manuel Ortega-Moral, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal:
An On-line Fisher Discriminant. ESANN 2005: 175-180 - [c40]Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal, Ali H. Sayed:
Steady state performance of convex combinations of adaptive filters. ICASSP (4) 2005: 33-36 - [c39]Pedro J. García-Laencina, Aníbal R. Figueiras-Vidal, Jesús Serrano-García, José-Luis Sancho-Gómez:
Exploiting Multitask Learning Schemes Using Private Subnetworks. IWANN 2005: 233-240 - [c38]Jerónimo Arenas-García, Vanessa Gómez-Verdejo, Sergio Muñoz-Romero, Manuel Ortega-Moral, Aníbal R. Figueiras-Vidal:
Fast Classification with Neural Networks via Confidence Rating. IWANN 2005: 622-629 - 2004
- [j30]Manel Martínez-Ramón, Antonio Artés-Rodríguez, Ángel Navia-Vázquez, Aníbal R. Figueiras-Vidal:
Adaptively combined LMS and logistic equalizers. IEEE Signal Process. Lett. 11(10): 777-779 (2004) - [j29]Alicia Guerrero-Curieses, Jesús Cid-Sueiro, Rocío Alaíz-Rodríguez, Aníbal R. Figueiras-Vidal:
Local estimation of posterior class probabilities to minimize classification errors. IEEE Trans. Neural Networks 15(2): 309-317 (2004) - [j28]José Luis Rojo-Álvarez, Luis Martínez-Ramón, Mario de Prado-Cumplido, Antonio Artés-Rodríguez, Aníbal R. Figueiras-Vidal:
Support vector method for robust ARMA system identification. IEEE Trans. Signal Process. 52(1): 155-164 (2004) - [j27]Ángel Navia-Vázquez, Fernando Pérez-Cruz, Antonio Artés-Rodríguez, Aníbal R. Figueiras-Vidal:
Advantages of Unbiased Support Vector Classifiers for Data Mining Applications. J. VLSI Signal Process. 37(2-3): 223-235 (2004) - 2003
- [j26]Emilio Parrado-Hernández, I. Mora-Jiménez, Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal, Ángel Navia-Vázquez:
Growing support vector classifiers with controlled complexity. Pattern Recognit. 36(7): 1479-1488 (2003) - [j25]José Luis Rojo-Álvarez, Manel Martínez-Ramón, Aníbal R. Figueiras-Vidal, Ana García Armada, Antonio Artés-Rodríguez:
A robust support vector algorithm for nonparametric spectral analysis. IEEE Signal Process. Lett. 10(11): 320-323 (2003) - [j24]Fernando Pérez-Cruz, Ángel Navia-Vázquez, Aníbal R. Figueiras-Vidal, Antonio Artés-Rodríguez:
Empirical risk minimization for support vector classifiers. IEEE Trans. Neural Networks 14(2): 296-303 (2003) - [j23]Sancho Salcedo-Sanz, Carlos Bousoño-Calzón, Aníbal R. Figueiras-Vidal:
A mixed neural-genetic algorithm for the broadcast scheduling problem. IEEE Trans. Wirel. Commun. 2(2): 277-283 (2003) - [c37]Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal, Amanda J. C. Sharkey:
The Beneficial Effects of Using Multi-net Systems That Focus on Hard Patterns. Multiple Classifier Systems 2003: 45-54 - [c36]Jerónimo Arenas-García, Vanessa Gómez-Verdejo, Manel Martínez-Ramón, Aníbal R. Figueiras-Vidal:
Separate-variable adaptive combination of LMS adaptive filters for plant identification. NNSP 2003: 239-248 - 2002
- [c35]Ascensión Gallardo-Antolín, Ángel Navia-Vázquez, Harold Y. Molina-Bulla, A. B. Rodríguez-González, Francisco J. Valverde-Albacete, Jesús Cid-Sueiro, Aníbal R. Figueiras-Vidal, T. Koutris, C. Xirouhaki, Manolis Koubarakis:
I-Gaia: an information processing layer for the DIET platform. AAMAS 2002: 1272-1279 - [c34]I. Mora-Jiménez, Abdelouahid Lyhyaoui, Jerónimo Arenas-García, Ángel Navia-Vázquez, Aníbal R. Figueiras-Vidal:
A Trainable Classifier via k Nearest Neighbors. HIS 2002: 365-373 - [c33]Fernando Pérez-Cruz, Gustavo Camps-Valls, Emilio Soria-Olivas, Juan José Pérez-Ruixo, Aníbal R. Figueiras-Vidal, Antonio Artés-Rodríguez:
Multi-dimensional Function Approximation and Regression Estimation. ICANN 2002: 757-762 - [c32]José Luis Rojo-Álvarez, Arcadi García-Alberola, Manel Martínez-Ramón, Mariano Valdés, Aníbal R. Figueiras-Vidal, Antonio Artés-Rodríguez:
Support Vector Robust Algorithms for Non-parametric Spectral Analysis. ICANN 2002: 1100-1105 - [c31]José Luis Rojo-Álvarez, Manel Martínez-Ramón, Aníbal R. Figueiras-Vidal, Mario de Prado-Cumplido, Antonio Artés-Rodríguez:
Support Vector Method for ARMA System Identification: A Robust Cost Interpretation. ICANN 2002: 1106-1111 - [c30]Manel Martínez-Ramón, Jerónimo Arenas-García, Ángel Navia-Vázquez, Aníbal R. Figueiras-Vidal:
An adaptive combination of adaptive filters for plant identification. DSP 2002: 1195-1198 - 2001
- [j22]Jesús Cid-Sueiro, Aníbal R. Figueiras-Vidal:
On the structure of strict sense Bayesian cost functions and its applications. IEEE Trans. Neural Networks 12(3): 445-455 (2001) - [j21]Ángel Navia-Vázquez, Fernando Pérez-Cruz, Antonio Artés-Rodríguez, Aníbal R. Figueiras-Vidal:
Weighted least squares training of support vector classifiers leading to compact and adaptive schemes. IEEE Trans. Neural Networks 12(5): 1047-1059 (2001) - [c29]Armando Malanda-Trigueros, Fernando Calleja-Garde, Aníbal R. Figueiras-Vidal:
A genetic algorithm for noisy channel color quantization design. ICIP (1) 2001: 898-901 - 2000
- [j20]José-Luis Sancho, William E. Pierson, Batu Ulug, Aníbal R. Figueiras-Vidal, Stanley C. Ahalt:
Class separability estimation and incremental learning using boundary methods. Neurocomputing 35(1-4): 3-26 (2000) - [j19]Ángel Navia-Vázquez, Aníbal R. Figueiras-Vidal:
Efficient Block Training of Multilayer Perceptrons. Neural Comput. 12(6): 1429-1447 (2000) - [j18]Jesús Cid-Sueiro, Luis M. San-José-Revuelta, Aníbal R. Figueiras-Vidal:
Soft-decision equalizers for in-service error rate monitoring. Signal Process. 80(4): 741-744 (2000) - [c28]Miguel A. Ferrer, Itziar G. Alonso-González, Carlos Manuel Travieso-González, Aníbal R. Figueiras-Vidal:
Improving generalization ability of HMM/NNs based classifiers. EUSIPCO 2000: 1-4 - [c27]Manel Martínez-Ramón, José-Luis Sancho-Gómez, Antonio Artés-Rodríguez, Aníbal R. Figueiras-Vidal:
Adaptive combination of LMS and logistic-linear equalizers to improve the speed-performance compromise. EUSIPCO 2000: 1-4
1990 – 1999
- 1999
- [j17]Ángel Navia-Vázquez, Aníbal R. Figueiras-Vidal:
Total least squares for block training of neural networks. Neurocomputing 25(1-3): 213-217 (1999) - [j16]Jesús Cid-Sueiro, Juan Ignacio Arribas, Sebastian Urban-Munoz, Aníbal R. Figueiras-Vidal:
Cost functions to estimate a posteriori probabilities in multiclass problems. IEEE Trans. Neural Networks 10(3): 645-656 (1999) - [j15]Abdelouahid Lyhyaoui, Manel Martínez-Ramón, Inma Mora, Maryan Vaquez, José-Luis Sancho, Aníbal R. Figueiras-Vidal:
Sample selection via clustering to construct support vector-like classifiers. IEEE Trans. Neural Networks 10(6): 1474-1481 (1999) - [c26]Juan Ignacio Arribas, Jesús Cid-Sueiro, Tülay Adali, Aníbal R. Figueiras-Vidal:
Neural networks to estimate ML multi-class constrained conditional probability density functions. IJCNN 1999: 1429-1432 - [c25]Juan Ignacio Arribas, Jesús Cid-Sueiro, Tülay Adali, Hongmei Ni, Bo Wang, Aníbal R. Figueiras-Vidal:
Estimates of constrained multi-class a posteriori probabilities in time series problems with neural networks. IJCNN 1999: 1560-1561 - [c24]Itziar G. Alonso-González, Carlos Manuel Travieso-González, Miguel Angel Ferrer-Ballester, Aníbal R. Figueiras-Vidal:
Improving a HMM Speech Recognizer with a Polynomial GMDH Neural Network Postprocessor. SIP 1999: 279-283 - 1998
- [j14]Francisco Javier González-Serrano, Aníbal R. Figueiras-Vidal, Antonio Artés-Rodríguez:
Fourier analysis of the generalized CMAC neural network. Neural Networks 11(3): 391-396 (1998) - [j13]Francisco Javier González-Serrano, Aníbal R. Figueiras-Vidal, Antonio Artés-Rodríguez:
Generalizing CMAC architecture and training. IEEE Trans. Neural Networks 9(6): 1509-1514 (1998) - [c23]Jesús Cid-Sueiro, Aníbal R. Figueiras-Vidal:
Non-linear equalizers that estimate error rates during reception. EUSIPCO 1998: 1-4 - [c22]Francisco Javier González-Serrano, Aníbal R. Figueiras-Vidal, Antonio Artés-Rodríguez:
GGMAC-based equalizer for nonlinear channels. ICASSP 1998: 1165-1168 - [c21]Armando Malanda-Trigueros, Aníbal R. Figueiras-Vidal:
A refinement algorithm for vector quantization codebook design. ICECS 1998: 235-238 - 1997
- [j12]Carlos Bousoño-Calzón, Aníbal R. Figueiras-Vidal:
A bank of Hopfield neural networks for the shortest path problem. Signal Process. 61(2): 157-170 (1997) - 1996
- [j11]Carlos J. Pantaleón-Prieto, Ignacio Santamaría-Caballero, Aníbal R. Figueiras-Vidal:
Competitive local linear modeling. Signal Process. 49(2): 73-83 (1996) - [j10]Antonio Artés-Rodríguez, Aníbal R. Figueiras-Vidal:
Wiener extrapolation of sequences and the expectation-maximization algorithm. IEEE Signal Process. Lett. 3(9): 260-262 (1996) - [c20]Aníbal R. Figueiras-Vidal, Antonio Artés-Rodríguez, Jesús Cid-Sueiro, Manel Martínez-Ramón:
Adaptive signal processing: A discussion of trade-offs from the perspective of artificial learning. EUSIPCO 1996: 1-6 - [c19]Francisco Javier González-Serrano, Aníbal R. Figueiras-Vidal, Antonio Artés-Rodríguez:
A fast LUT+CMAC data predistorter. EUSIPCO 1996: 1-4 - [c18]Armando Malanda, Aníbal R. Figueiras-Vidal, G. Cain:
Adaptive+darwinian approach for the estimation and tracking of time delays. EUSIPCO 1996: 1-4 - 1995
- [j9]Miguel Angel Ferrer-Ballester, Aníbal R. Figueiras-Vidal:
Efficient adaptive vector quantization of LPC parameters. IEEE Trans. Speech Audio Process. 3(4): 314-317 (1995) - [j8]Luis Castedo, Aníbal R. Figueiras-Vidal:
An adaptive beamforming technique based on cyclostationary signal properties. IEEE Trans. Signal Process. 43(7): 1637-1650 (1995) - 1994
- [j7]Jesús Cid-Sueiro, Antonio Artés-Rodríguez, Aníbal R. Figueiras-Vidal:
Recurrent radial basis function networks for optimal symbol-by-symbol equalization. Signal Process. 40(1): 53-63 (1994) - [c17]Luis Castedo, Ching-Yih Tseng, Aníbal R. Figueiras-Vidal, Lloyd J. Griffiths:
Linearly-constrained adaptive beamforming using cyclostationary signal properties. ICASSP (4) 1994: 249-252 - [c16]Miguel Angel Ferrer-Ballester, Aníbal R. Figueiras-Vidal:
Improving CELP voice quality by projection similarity measure. ICSLP 1994: 2063-2066 - 1993
- [c15]Juan Antonio Hernández-Méndez, Aníbal R. Figueiras-Vidal:
Measuring similarities among speakers by means of neural networks. EUROSPEECH 1993: 643-646 - [c14]Carlos Pantaleón, Aníbal R. Figueiras-Vidal:
Nonlinear Time Series Modeling by Competitive Segmentation of State Space. IWANN 1993: 525-530 - [c13]Jesús Cid-Sueiro, Luis Weruaga-Prieto, Aníbal R. Figueiras-Vidal:
Optimal Blind Equalization of Gaussian Channels. IWANN 1993: 605-610 - 1992
- [j6]Vito Cappellini, Aníbal R. Figueiras-Vidal:
Guest Editorial. Eur. Trans. Telecommun. 3(6): 546 (1992) - [j5]Aníbal R. Figueiras-Vidal:
Correction to 'Comments on 'A curiosum concerning discrete time convolution', ' plus a remark. IEEE Trans. Signal Process. 40(6): 1575 (1992) - [c12]Luis Weruaga-Prieto, Jesús Cid-Sueiro, Aníbal R. Figueiras-Vidal:
Optimal variable step LMS look-up-table plus transversal filter nonlinear echo cancellers. ICASSP 1992: 229-232 - 1991
- [j4]Aníbal R. Figueiras-Vidal:
Comments on 'A curiosum concerning discrete time convolution' [by E.B. Hall and G.L. Wise]. IEEE Trans. Signal Process. 39(6): 1426 (1991) - [c11]Aníbal R. Figueiras-Vidal, Antonio Artés-Rodríguez, Juan Antonio A. Hernández-Méndez:
Phase constraining algorithms for data blind equalization. ICASSP 1991: 1929-1932 - 1990
- [j3]Aníbal R. Figueiras-Vidal, Domingo Docampo-Amoedo, José R. Casar Corredera, Antonio Artés-Rodríguez:
Adaptive iterative algorithms for spiky deconvolution. IEEE Trans. Acoust. Speech Signal Process. 38(8): 1462-1466 (1990) - [c10]Aníbal R. Figueiras-Vidal, Domingo Docampo-Amoedo, José R. Casar Corredera, Antonio Artés-Rodríguez:
On using the adaptive delay filter in sparse identification and extensions to sparse deconvolution and sinusoid detection. ICASSP 1990: 2503-2506
1980 – 1989
- 1989
- [c9]Domingo Docampo-Amoedo, Aníbal R. Figueiras-Vidal:
A deconvolution approach to harmonic signal extrapolation. ICASSP 1989: 2345-2348 - 1988
- [c8]Aníbal R. Figueiras-Vidal, José Manuel Páez-Borrallo, Francisco Lorenz Speranzini:
Non-quadratic recursive algorithms (RLK) for transversal plant identification. ICASSP 1988: 1395-1398 - 1987
- [j2]Aníbal R. Figueiras-Vidal, José Manuel Páez-Borrallo, Ramón García Gómez:
On using cooccurrence matrices to detect periodicities. IEEE Trans. Acoust. Speech Signal Process. 35(1): 114-116 (1987) - [c7]José Manuel Páez-Borrallo, Aníbal R. Figueiras-Vidal, Luis Vergara-Dominguez:
Analysis of LK frequency-adaptive transversal filters in plant identification. ICASSP 1987: 427-430 - [c6]L. Vergara-Domínguez, Aníbal R. Figueiras-Vidal:
A new class of high-order Yule-Walker estimates. ICASSP 1987: 1011-1014 - 1986
- [c5]Luis A. Hernández Gómez, Francisco Javier Casajús-Quirós, Aníbal R. Figueiras-Vidal, Ramón García-Gómez:
On the behaviour of reduced complexity code-excited linear prediction (CELP). ICASSP 1986: 469-472 - [c4]Ramón García-Gómez, Jesús M. Alcázar-Fernández, Aníbal R. Figueiras-Vidal:
Envelope constrained multipulse speech coding. ICASSP 1986: 3051-3054 - 1985
- [c3]Aníbal R. Figueiras-Vidal, José R. Casar Corredera, Ramón García-Gómez, José Manuel Páez-Borrallo:
L1-Norm versus L2-Norm minimization in parametric spectral analysis: A general discussion. ICASSP 1985: 304-307 - [c2]Jesús M. Alcázar-Fernández, José R. Casar Corredera, Aníbal R. Figueiras-Vidal:
On absolute value minimization approaches to tauberian modelling. ICASSP 1985: 461-464 - [c1]José R. Casar Corredera, Mariano García Otero, Aníbal R. Figueiras-Vidal:
Data echo nonlinear cancellation. ICASSP 1985: 1245-1248 - 1980
- [j1]Aníbal R. Figueiras-Vidal, Jose B. Marino-Acebal, Miguel A. Lagunas-Hernandez:
Comments on and Extensions of Wolf's Signal-to-Channel Noise Formulas for Delta-Modulated Systems. IEEE Trans. Commun. 28(1): 131-135 (1980)
Coauthor Index
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