Aníbal R. Figueiras-Vidal

ORCID

Publication Activity (10 Years)

Years Active: 1980-2023
Publications (10 Years): 38

Top Venues

Publications

Javier Mediavilla-Relaño, Marcelino Lázaro, Aníbal R. Figueiras-Vidal
Imbalance example-dependent cost classification: A Bayesian based method. Expert Syst. Appl. 213 (Part) (2023)
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 (2023)
Marcelino Lázaro, Aníbal R. Figueiras-Vidal
Neural network for ordinal classification of imbalanced data by minimizing a Bayesian cost. Pattern Recognit. 137 (2023)
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)
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) (2021)
Adrián Sánchez-Morales, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal
Complete autoencoders for classification with missing values. Neural Comput. Appl. 33 (6) (2021)
Marcelino Lázaro, Aníbal R. Figueiras-Vidal
A Bayes Risk Minimization Machine for Example-Dependent Cost Classification. IEEE Trans. Cybern. 51 (7) (2021)
Alexander Benítez-Buenache, Lorena Álvarez-Pérez, Aníbal R. Figueiras-Vidal
On the design of Bayesian principled algorithms for imbalanced classification. Knowl. Based Syst. 221 (2021)
Aitor Gutiérrez-López, Francisco Javier González-Serrano, Aníbal R. Figueiras-Vidal
Asymmetric label switching resists binary imbalance. Inf. Fusion 60 (2020)
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 (2020)
Marcelino Lázaro, Francisco Herrera, Aníbal R. Figueiras-Vidal
Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification. Inf. Sci. 520 (2020)
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 (2020)
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) (2020)
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 (2020)
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 (2020)
Ricardo F. Alvear-Sandoval, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal
On improving CNNs performance: The case of MNIST. Inf. Fusion 52 (2019)
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)
Adrián Sánchez-Morales, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal
Exploiting label information to improve auto-encoding based classifiers. Neurocomputing 370 (2019)
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)
Alexander Benítez-Buenache, Lorena Álvarez-Pérez, V. John Mathews, Aníbal R. Figueiras-Vidal
Likelihood ratio equivalence and imbalanced binary classification. Expert Syst. Appl. 130 (2019)
José-Luis Sancho-Gómez, Juan-Antonio Martínez-García, Stanley C. Ahalt, Aníbal R. Figueiras-Vidal
Linear discriminants described by disjoint tangent configurations. Neurocomputing 316 (2018)
Ricardo F. Alvear-Sandoval, Aníbal R. Figueiras-Vidal
On building ensembles of stacked denoising auto-encoding classifiers and their further improvement. Inf. Fusion 39 (2018)
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 (2018)
David Díaz-Vico, Aníbal R. Figueiras-Vidal, José R. Dorronsoro
Deep MLPs for Imbalanced Classification. IJCNN (2018)
Marcelino Lázaro, Monson H. Hayes, Aníbal R. Figueiras-Vidal
Training neural network classifiers through Bayes risk minimization applying unidimensional Parzen windows. Pattern Recognit. 77 (2018)
Adrián Sánchez-Morales, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal
Values Deletion to Improve Deep Imputation Processes. IWINAC (2) (2017)
Anas Ahachad, Lorena Álvarez-Pérez, Aníbal R. Figueiras-Vidal
Boosting ensembles with controlled emphasis intensity. Pattern Recognit. Lett. 88 (2017)
Francisco Javier González-Serrano, Aníbal R. Figueiras-Vidal
Generalized CMAC adaptive ensembles for concept-drifting data streams. EUSIPCO (2017)
Lorena Álvarez-Pérez, Anas Ahachad, Aníbal R. Figueiras-Vidal
Pre-emphasizing Binarized Ensembles to Improve Classification Performance. IWANN (1) (2017)
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 (2017)
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) (2016)
Ricardo F. Alvear-Sandoval, Aníbal R. Figueiras-Vidal
An Experiment in Pre-Emphasizing Diversified Deep Neural Classifiers. ESANN (2016)
Manuel Montoya-Catala, Ricardo F. Alvear-Sandoval, Aníbal R. Figueiras-Vidal
Experiments in combining boosting and deep stacked networks. MLSP (2016)
Marcelino Lázaro, Francisco Herrera, Aníbal R. Figueiras-Vidal
Classification of Binary Imbalanced Data Using A Bayesian Ensemble of Bayesian Neural Networks. EANN (2015)
Efraín Mayhua-López, Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal
A new boosting design of Support Vector Machine classifiers. Inf. Fusion 25 (2015)
Adil Omari, Aníbal R. Figueiras-Vidal
Post-aggregation of classifier ensembles. Inf. Fusion 26 (2015)
R. F. Alvear-Sandoval, Aníbal R. Figueiras-Vidal
Does diversity improve deep learning? EUSIPCO (2015)
Anas Ahachad, Adil Omari, Aníbal R. Figueiras-Vidal
Neighborhood Guided Smoothed Emphasis for Real Adaboost Ensembles. Neural Process. Lett. 42 (1) (2015)
Luis Munoz-Gonzalez, Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal
Laplace approximation with Gaussian Processes for volatility forecasting. CIP (2014)
Luis Munoz-Gonzalez, Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal
Divisive Gaussian Processes for Nonstationary Regression. IEEE Trans. Neural Networks Learn. Syst. 25 (11) (2014)
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) (2013)
Anas Ahachad, Adil Omari, Aníbal R. Figueiras-Vidal
Smoothed Emphasis for Boosting Ensembles. IWANN (1) (2013)
Adil Omari, Aníbal R. Figueiras-Vidal
Feature Combiners With Gate-Generated Weights for Classification. IEEE Trans. Neural Networks Learn. Syst. 24 (1) (2013)
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) (2013)
Efraín Mayhua-López, Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal
Real AdaBoost With Gate Controlled Fusion. IEEE Trans. Neural Networks Learn. Syst. 23 (12) (2012)
Aníbal R. Figueiras-Vidal, Lior Rokach
An Exploration of Research Directions in Machine Ensemble Theory and Applications. ESANN (2012)
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)
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) (2011)
Luis Munoz-Gonzalez, Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal
Heteroscedastic Gaussian process regression using expectation propagation. MLSP (2011)
Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal
Marginalized neural network mixtures for large-scale regression. IEEE Trans. Neural Networks 21 (8) (2010)
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) (2010)
Soufiane El Jelali, Abdelouahid Lyhyaoui, Aníbal R. Figueiras-Vidal
A pseudoregression formulation of emphasized soft target procedures for classification problems. ESANN (2010)
Vanessa Gómez-Verdejo, Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal
Committees of Adaboost ensembles with modified emphasis functions. Neurocomputing 73 (7-9) (2010)
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)
Miguel Lázaro-Gredilla, Joaquin Quiñonero Candela, Carl Edward Rasmussen, Aníbal R. Figueiras-Vidal
Sparse Spectrum Gaussian Process Regression. J. Mach. Learn. Res. 11 (2010)
Efraín Mayhua-López, Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal
Improving boosting performance with a local combination of learners. IJCNN (2010)
Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal
Pattern classification with missing data: a review. Neural Comput. Appl. 19 (2) (2010)
Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal
Adaptive Combination of Proportionate Filters for Sparse Echo Cancellation. IEEE Trans. Speech Audio Process. 17 (6) (2009)
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) (2009)
I. Mora-Jiménez, Aníbal R. Figueiras-Vidal
Improving performance of neural classifiers via selective reduction of target levels. Neurocomputing 72 (13-15) (2009)
Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal
Inter-domain Gaussian Processes for Sparse Inference using Inducing Features. NIPS (2009)
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) (2009)
Soufiane El Jelali, Abdelouahid Lyhyaoui, Aníbal R. Figueiras-Vidal
Designing Model Based Classifiers by Emphasizing Soft Targets. Fundam. Informaticae 96 (4) (2009)
Soufiane El Jelali, Abdelouahid Lyhyaoui, Aníbal R. Figueiras-Vidal
An emphasized target smoothing procedure to improve MLP classifiers performance. ESANN (2008)
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)
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)
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) (2008)
Theodoros Evgeniou, Aníbal R. Figueiras-Vidal, Sergios Theodoridis
Emerging Machine Learning Techniques in Signal Processing. EURASIP J. Adv. Signal Process. 2008 (2008)
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)
Soufiane El Jelali, Abdelouahid Lyhyaoui, Aníbal R. Figueiras-Vidal
Applying emphasized soft targets for Gaussian Mixture Model based classification. IMCSIT (2008)
Jaisiel Madrid-Sánchez, Miguel Lázaro-Gredilla, Aníbal R. Figueiras-Vidal
A Single Layer Perceptron Approach to Selective Multi-task Learning. IWINAC (1) (2007)
Jerónimo Arenas-García, Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal
Fast evaluation of neural networks via confidence rating. Neurocomputing 70 (16-18) (2007)
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)
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)
Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal
Improved Blind Equalization via Adaptive Combination of Constant Modulus Algorithms. ICASSP (3) (2006)
Vanessa Gómez-Verdejo, Aníbal R. Figueiras-Vidal
Designing neural network committees by combining boosting ensembles. ESANN (2006)
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)
Pedro J. García-Laencina, José-Luis Sancho-Gómez, Aníbal R. Figueiras-Vidal
Pattern Classification with Missing Values using Multitask Learning. IJCNN (2006)
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) (2006)
Vanessa Gómez-Verdejo, Manuel Ortega-Moral, Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal
Boosting by weighting critical and erroneous samples. Neurocomputing 69 (7-9) (2006)
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) (2006)
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) (2006)
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) (2005)
Vanessa Gómez-Verdejo, Manuel Ortega-Moral, Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal
Boosting by weighting boundary and erroneous samples. ESANN (2005)
Manuel Ortega-Moral, Vanessa Gómez-Verdejo, Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal
An On-line Fisher Discriminant. ESANN (2005)
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) (2005)
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)
Pedro J. García-Laencina, Aníbal R. Figueiras-Vidal, Jesús Serrano-García, José-Luis Sancho-Gómez
Exploiting Multitask Learning Schemes Using Private Subnetworks. IWANN (2005)
Jerónimo Arenas-García, Aníbal R. Figueiras-Vidal, Ali H. Sayed
Steady state performance of convex combinations of adaptive filters. ICASSP (4) (2005)
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) (2004)
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) (2004)
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) (2004)
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) (2004)
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) (2003)
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) (2003)
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)
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) (2003)
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)
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) (2003)
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)

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Publication Activity (10 Years)

Top Topics

Top Venues

Aníbal R. Figueiras-Vidal