Aníbal R. Figueiras-Vidal

According to our database1, Aníbal R. Figueiras-Vidal authored at least 124 papers between 1987 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Awards

IEEE Fellow

IEEE Fellow 2012, "For leadership in digital signal processing".

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2019
On improving CNNs performance: The case of MNIST.
Information Fusion, 2019

Exploiting label information to improve auto-encoding based classifiers.
Neurocomputing, 2019

Likelihood ratio equivalence and imbalanced binary classification.
Expert Syst. Appl., 2019

A Principled Two-Step Method for Example-Dependent Cost Binary Classification.
Proceedings of the From Bioinspired Systems and Biomedical Applications to Machine Learning, 2019

Machine-Health Application Based on Machine Learning Techniques for Prediction of Valve Wear in a Manufacturing Plant.
Proceedings of the From Bioinspired Systems and Biomedical Applications to Machine Learning, 2019

2018
Training neural network classifiers through Bayes risk minimization applying unidimensional Parzen windows.
Pattern Recognition, 2018

On building ensembles of stacked denoising auto-encoding classifiers and their further improvement - a correction.
Information Fusion, 2018

On building ensembles of stacked denoising auto-encoding classifiers and their further improvement.
Information Fusion, 2018

Linear discriminants described by disjoint tangent configurations.
Neurocomputing, 2018

Deep MLPs for Imbalanced Classification.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017
Boosting ensembles with controlled emphasis intensity.
Pattern Recognition Letters, 2017

Class Switching according to Nearest Enemy Distance for learning from highly imbalanced data-sets.
Pattern Recognition, 2017

Values Deletion to Improve Deep Imputation Processes.
Proceedings of the Biomedical Applications Based on Natural and Artificial Computing, 2017

Pre-emphasizing Binarized Ensembles to Improve Classification Performance.
Proceedings of the Advances in Computational Intelligence, 2017

Generalized CMAC adaptive ensembles for concept-drifting data streams.
Proceedings of the 25th European Signal Processing Conference, 2017

2016
Laplace Approximation for Divisive Gaussian Processes for Nonstationary Regression.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Experiments in combining boosting and deep stacked networks.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

An Experiment in Pre-Emphasizing Diversified Deep Neural Classifiers.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
Neighborhood Guided Smoothed Emphasis for Real Adaboost Ensembles.
Neural Processing Letters, 2015

Post-aggregation of classifier ensembles.
Information Fusion, 2015

A new boosting design of Support Vector Machine classifiers.
Information Fusion, 2015

Does diversity improve deep learning?
Proceedings of the 23rd European Signal Processing Conference, 2015

Classification of Binary Imbalanced Data Using A Bayesian Ensemble of Bayesian Neural Networks.
Proceedings of the Engineering Applications of Neural Networks, 2015

2014
Divisive Gaussian Processes for Nonstationary Regression.
IEEE Trans. Neural Netw. Learning Syst., 2014

Laplace approximation with Gaussian Processes for volatility forecasting.
Proceedings of the 4th International Workshop on Cognitive Information Processing, 2014

2013
Enhanced Adaptive Volterra Filtering by Automatic Attenuation of Memory Regions and Its Application to Acoustic Echo Cancellation.
IEEE Trans. Signal Processing, 2013

Feature Combiners With Gate-Generated Weights for Classification.
IEEE Trans. Neural Netw. Learning Syst., 2013

Classifying patterns with missing values using Multi-Task Learning perceptrons.
Expert Syst. Appl., 2013

Smoothed Emphasis for Boosting Ensembles.
Proceedings of the Advances in Computational Intelligence, 2013

2012
Real AdaBoost With Gate Controlled Fusion.
IEEE Trans. Neural Netw. Learning Syst., 2012

An Exploration of Research Directions in Machine Ensemble Theory and Applications.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011
Adaptive Combination of Volterra Kernels and Its Application to Nonlinear Acoustic Echo Cancellation.
IEEE Trans. Audio, Speech & Language Processing, 2011

Heteroscedastic Gaussian process regression using expectation propagation.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

A block-based approach to adaptively bias the weights of adaptive filters.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

2010
Adaptively biasing the weights of adaptive filters.
IEEE Trans. Signal Processing, 2010

Marginalized neural network mixtures for large-scale regression.
IEEE Trans. Neural Networks, 2010

Pattern classification with missing data: a review.
Neural Computing and Applications, 2010

Sparse Spectrum Gaussian Process Regression.
J. Mach. Learn. Res., 2010

Committees of Adaboost ensembles with modified emphasis functions.
Neurocomputing, 2010

Least-squares adaptation of affine combinations of multiple adaptive filters.
Proceedings of the International Symposium on Circuits and Systems (ISCAS 2010), May 30, 2010

Improving boosting performance with a local combination of learners.
Proceedings of the International Joint Conference on Neural Networks, 2010

A pseudoregression formulation of emphasized soft target procedures for classification problems.
Proceedings of the ESANN 2010, 2010

2009
Adaptive Combination of Proportionate Filters for Sparse Echo Cancellation.
IEEE Trans. Audio, Speech & Language Processing, 2009

Improving performance of neural classifiers via selective reduction of target levels.
Neurocomputing, 2009

K nearest neighbours with mutual information for simultaneous classification and missing data imputation.
Neurocomputing, 2009

Combining Missing Data Imputation and Pattern Classification in a Multi-Layer Perceptron.
Intelligent Automation & Soft Computing, 2009

Designing Model Based Classifiers by Emphasizing Soft Targets.
Fundam. Inform., 2009

Inter-domain Gaussian Processes for Sparse Inference using Inducing Features.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008
A Dynamically Adjusted Mixed Emphasis Method for Building Boosting Ensembles.
IEEE Trans. Neural Networks, 2008

Sparse Deconvolution Using Support Vector Machines.
EURASIP J. Adv. Sig. Proc., 2008

Emerging Machine Learning Techniques in Signal Processing.
EURASIP J. Adv. Sig. Proc., 2008

Applying emphasized soft targets for Gaussian Mixture Model based classification.
Proceedings of the International Multiconference on Computer Science and Information Technology, 2008

A normalized adaptation scheme for the convex combination of two adaptive filters.
Proceedings of the IEEE International Conference on Acoustics, 2008

An emphasized target smoothing procedure to improve MLP classifiers performance.
Proceedings of the ESANN 2008, 2008

K-nearest neighbours based on mutual information for incomplete data classification.
Proceedings of the ESANN 2008, 2008

2007
Fast evaluation of neural networks via confidence rating.
Neurocomputing, 2007

A Single Layer Perceptron Approach to Selective Multi-task Learning.
Proceedings of the Bio-inspired Modeling of Cognitive Tasks, 2007

Multi-task Neural Networks for Dealing with Missing Inputs.
Proceedings of the Bio-inspired Modeling of Cognitive Tasks, 2007

A New Cost Function for Binary Classification Problems Based on the Distributions of the Soft Output for Each Class.
Proceedings of the International Joint Conference on Neural Networks, 2007

2006
Mean-square performance of a convex combination of two adaptive filters.
IEEE Trans. Signal Processing, 2006

Support Vector Machines for Nonlinear Kernel ARMA System Identification.
IEEE Trans. Neural Networks, 2006

Plant identification via adaptive combination of transversal filters.
Signal Processing, 2006

Boosting by weighting critical and erroneous samples.
Neurocomputing, 2006

Pattern Classification with Missing Values using Multitask Learning.
Proceedings of the International Joint Conference on Neural Networks, 2006

Improved Blind Equalization via Adaptive Combination of Constant Modulus Algorithms.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

A new cost function to build MLPs by means of regularized boosting.
Proceedings of the Second IASTED International Conference on Computational Intelligence, 2006

Designing neural network committees by combining boosting ensembles.
Proceedings of the ESANN 2006, 2006

2005
New algorithms for improved adaptive convex combination of LMS transversal filters.
IEEE Trans. Instrumentation and Measurement, 2005

Support vector machines framework for linear signal processing.
Signal Processing, 2005

Exploiting Multitask Learning Schemes Using Private Subnetworks.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Fast Classification with Neural Networks via Confidence Rating.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Steady state performance of convex combinations of adaptive filters.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

An On-line Fisher Discriminant.
Proceedings of the ESANN 2005, 2005

Boosting by weighting boundary and erroneous samples.
Proceedings of the ESANN 2005, 2005

2004
Advantages of Unbiased Support Vector Classifiers for Data Mining Applications.
VLSI Signal Processing, 2004

Support vector method for robust ARMA system identification.
IEEE Trans. Signal Processing, 2004

Local estimation of posterior class probabilities to minimize classification errors.
IEEE Trans. Neural Networks, 2004

Adaptively combined LMS and logistic equalizers.
IEEE Signal Process. Lett., 2004

2003
A mixed neural-genetic algorithm for the broadcast scheduling problem.
IEEE Trans. Wireless Communications, 2003

Empirical risk minimization for support vector classifiers.
IEEE Trans. Neural Networks, 2003

Growing support vector classifiers with controlled complexity.
Pattern Recognition, 2003

Separate-variable adaptive combination of LMS adaptive filters for plant identification.
Proceedings of the NNSP 2003, 2003

The Beneficial Effects of Using Multi-net Systems That Focus on Hard Patterns.
Proceedings of the Multiple Classifier Systems, 4th International Workshop, 2003

2002
Support Vector Method for ARMA System Identification: A Robust Cost Interpretation.
Proceedings of the Artificial Neural Networks, 2002

Support Vector Robust Algorithms for Non-parametric Spectral Analysis.
Proceedings of the Artificial Neural Networks, 2002

Multi-dimensional Function Approximation and Regression Estimation.
Proceedings of the Artificial Neural Networks, 2002

A Trainable Classifier via k Nearest Neighbors.
Proceedings of the Soft Computing Systems - Design, Management and Applications, 2002

I-Gaia: an information processing layer for the DIET platform.
Proceedings of the First International Joint Conference on Autonomous Agents & Multiagent Systems, 2002

2001
Weighted least squares training of support vector classifiers leading to compact and adaptive schemes.
IEEE Trans. Neural Networks, 2001

On the structure of strict sense Bayesian cost functions and its applications.
IEEE Trans. Neural Networks, 2001

A genetic algorithm for noisy channel color quantization design.
Proceedings of the 2001 International Conference on Image Processing, 2001

2000
Soft-decision equalizers for in-service error rate monitoring.
Signal Processing, 2000

Efficient Block Training of Multilayer Perceptrons.
Neural Computation, 2000

Class separability estimation and incremental learning using boundary methods.
Neurocomputing, 2000

Adaptive combination of LMS and logistic-linear equalizers to improve the speed-performance compromise.
Proceedings of the 10th European Signal Processing Conference, 2000

Improving generalization ability of HMM/NNs based classifiers.
Proceedings of the 10th European Signal Processing Conference, 2000

1999
Sample selection via clustering to construct support vector-like classifiers.
IEEE Trans. Neural Networks, 1999

Cost functions to estimate a posteriori probabilities in multiclass problems.
IEEE Trans. Neural Networks, 1999

Total least squares for block training of neural networks.
Neurocomputing, 1999

Improving a HMM Speech Recognizer with a Polynomial GMDH Neural Network Postprocessor.
Proceedings of the Signal and Image Processing (SIP), 1999

Estimates of constrained multi-class a posteriori probabilities in time series problems with neural networks.
Proceedings of the International Joint Conference Neural Networks, 1999

Neural networks to estimate ML multi-class constrained conditional probability density functions.
Proceedings of the International Joint Conference Neural Networks, 1999

1998
Generalizing CMAC architecture and training.
IEEE Trans. Neural Networks, 1998

Fourier analysis of the generalized CMAC neural network.
Neural Networks, 1998

GGMAC-based equalizer for nonlinear channels.
Proceedings of the 1998 IEEE International Conference on Acoustics, 1998

Non-linear equalizers that estimate error rates during reception.
Proceedings of the 9th European Signal Processing Conference, 1998

1997
A bank of Hopfield neural networks for the shortest path problem.
Signal Processing, 1997

1996
Competitive local linear modeling.
Signal Processing, 1996

Adaptive+darwinian approach for the estimation and tracking of time delays.
Proceedings of the 8th European Signal Processing Conference, 1996

A fast LUT+CMAC data predistorter.
Proceedings of the 8th European Signal Processing Conference, 1996

Adaptive signal processing: A discussion of trade-offs from the perspective of artificial learning.
Proceedings of the 8th European Signal Processing Conference, 1996

1995
An adaptive beamforming technique based on cyclostationary signal properties.
IEEE Trans. Signal Processing, 1995

Efficient adaptive vector quantization of LPC parameters.
IEEE Trans. Speech and Audio Processing, 1995

1994
Recurrent radial basis function networks for optimal symbol-by-symbol equalization.
Signal Processing, 1994

Improving CELP voice quality by projection similarity measure.
Proceedings of the 3rd International Conference on Spoken Language Processing, 1994

Linearly-constrained adaptive beamforming using cyclostationary signal properties.
Proceedings of ICASSP '94: IEEE International Conference on Acoustics, 1994

1993
Nonlinear Time Series Modeling by Competitive Segmentation of State Space.
Proceedings of the New Trends in Neural Computation, 1993

Optimal Blind Equalization of Gaussian Channels.
Proceedings of the New Trends in Neural Computation, 1993

Measuring similarities among speakers by means of neural networks.
Proceedings of the Third European Conference on Speech Communication and Technology, 1993

1992
Correction to 'Comments on 'A curiosum concerning discrete time convolution', ' plus a remark.
IEEE Trans. Signal Processing, 1992

Guest Editorial.
European Transactions on Telecommunications, 1992

1991
Comments on 'A curiosum concerning discrete time convolution' [by E.B. Hall and G.L. Wise].
IEEE Trans. Signal Processing, 1991

1990
Adaptive iterative algorithms for spiky deconvolution.
IEEE Trans. Acoustics, Speech, and Signal Processing, 1990

1987
On using cooccurrence matrices to detect periodicities.
IEEE Trans. Acoustics, Speech, and Signal Processing, 1987


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