Alberto Suárez

José Luis Torrecilla

Miguel Carbajo-Berrocal

Pablo Marcos

J. Stat. Softw., 2024

2023

Relation between PLS and OLS regression in terms of the eigenvalue distribution of the regressor covariance matrix.

[BibT_eX]

[DOI]

David del Val

José R. Berrendero

CoRR, 2023

2022

Correction to: Building heterogeneous ensembles by pooling homogeneous ensembles.

[BibT_eX]

[DOI]

Int. J. Mach. Learn. Cybern., 2022

Building heterogeneous ensembles by pooling homogeneous ensembles.

[BibT_eX]

[DOI]

Int. J. Mach. Learn. Cybern., 2022

scikit-fda: A Python Package for Functional Data Analysis.

[BibT_eX]

[DOI]

José Luis Torrecilla

Miguel Carbajo-Berrocal

Pablo Marcos

CoRR, 2022

scikit-fda: Computational Tools for Machine Learning with Functional Data.

[BibT_eX]

[DOI]

Proceedings of the 34th IEEE International Conference on Tools with Artificial Intelligence, 2022

Classification of Functional Data: A Comparative Study.

[BibT_eX]

[DOI]

José Luis Torrecilla

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

SVM Ensembles on a Budget.

[BibT_eX]

[DOI]

David Nevado

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

2021

Objective functions from Bayesian optimization to locate additional drillholes.

[BibT_eX]

[DOI]

Bahram Jafrasteh

Comput. Geosci., 2021

2020

Optimal classification of Gaussian processes in homo- and heteroscedastic settings.

[BibT_eX]

[DOI]

José L. Torrecilla

Manuel A. Sánchez-Montañés

Stat. Comput., 2020

2019

Non-linear Causal Inference Using Gaussianity Measures.

[BibT_eX]

[DOI]

David Lopez-Paz

Proceedings of the Cause Effect Pairs in Machine Learning, 2019

2018

Vote-boosting ensembles.

[BibT_eX]

[DOI]

Pattern Recognit., 2018

A two-stage ensemble method for the detection of class-label noise.

[BibT_eX]

[DOI]

Neurocomputing, 2018

Pooling homogeneous ensembles to build heterogeneous ensembles.

[BibT_eX]

[DOI]

CoRR, 2018

Randomization vs Optimization in SVM Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Directional Data Analysis for Shape Classification.

[BibT_eX]

[DOI]

Adrián Muñoz

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Energy-Based Clustering for Pruning Heterogeneous Ensembles.

[BibT_eX]

[DOI]

Javier Cela

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

2017

Class Switching Ensembles for Ordinal Regression.

[BibT_eX]

[DOI]

Pedro Antonio Gutiérrez

María Pérez-Ortiz

Proceedings of the Advances in Computational Intelligence, 2017

2016

Non-linear Causal Inference using Gaussianity Measures.

[BibT_eX]

[DOI]

David Lopez-Paz

J. Mach. Learn. Res., 2016

Feature selection in functional data classification with recursive maxima hunting.

[BibT_eX]

[DOI]

José L. Torrecilla

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

An urn model for majority voting in classification ensembles.

[BibT_eX]

[DOI]

Víctor Soto

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Expectation propagation in linear regression models with spike-and-slab priors.

[BibT_eX]

[DOI]

Mach. Learn., 2015

Small margin ensembles can be robust to class-label noise.

[BibT_eX]

[DOI]

Neurocomputing, 2015

A memetic algorithm for cardinality-constrained portfolio optimization with transaction costs.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2015

2014

A Double Pruning Scheme for Boosting Ensembles.

[BibT_eX]

[DOI]

Víctor Soto

Sergio García-Moratilla

IEEE Trans. Cybern., 2014

Percentiles of sums of heavy-tailed random variables: beyond the single-loss approximation.

[BibT_eX]

[DOI]

Lorenzo Hernández

Jorge Tejero

Santiago Carrillo-Menéndez

Stat. Comput., 2014

Improving the Robustness of Bagging with Reduced Sampling Size.

[BibT_eX]

[DOI]

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013

How large should ensembles of classifiers be?

[BibT_eX]

[DOI]

Pattern Recognit., 2013

Critical sample size for the Lp-norm estimator in linear regression models.

[BibT_eX]

[DOI]

Alejandro Llorente

Proceedings of the Winter Simulations Conference: Simulation Making Decisions in a Complex World, 2013

Statistical Tests for the Detection of the Arrow of Time in Vector Autoregressive Models.

[BibT_eX]

[DOI]

Santiago Carrillo-Menéndez

Proceedings of the IJCAI 2013, 2013

2012

Robust quantification of the exposure to operational risk: Bringing economic sense to economic capital.

[BibT_eX]

[DOI]

Comput. Oper. Res., 2012

On the Independence of the Individual Predictions in Parallel Randomized Ensembles.

[BibT_eX]

[DOI]

Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011

Inference on the prediction of ensembles of infinite size.

[BibT_eX]

[DOI]

Pattern Recognit., 2011

Network-based sparse Bayesian classification.

[BibT_eX]

[DOI]

Pattern Recognit., 2011

Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles.

[BibT_eX]

[DOI]

Neurocomputing, 2011

Semiparametric bivariate Archimedean copulas.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2011

Gaussianity Measures for Detecting the Direction of Causal Time Series.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2011, 2011

The TransRAR crossover operator for genetic algorithms with set encoding.

[BibT_eX]

[DOI]

Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

2010

Expectation Propagation for microarray data classification.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2010

Out-of-bag estimation of the optimal sample size in bagging.

[BibT_eX]

[DOI]

Pattern Recognit., 2010

Hybrid Approaches and Dimensionality Reduction for Portfolio Selection with Cardinality Constraints.

[BibT_eX]

[DOI]

IEEE Comput. Intell. Mag., 2010

A Double Pruning Algorithm for Classification Ensembles.

[BibT_eX]

[DOI]

Víctor Soto

Proceedings of the Multiple Classifier Systems, 9th International Workshop, 2010

2009

An Analysis of Ensemble Pruning Techniques Based on Ordered Aggregation.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2009

Statistical Instance-Based Pruning in Ensembles of Independent Classifiers.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2009

A hybrid optimization approach to index tracking.

[BibT_eX]

[DOI]

Ann. Oper. Res., 2009

Statistical Instance-Based Ensemble Pruning for Multi-class Problems.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2009

2008

Class-switching neural network ensembles.

[BibT_eX]

[DOI]

Aitor Sánchez-Martínez

Neurocomputing, 2008

2007

Using boosting to prune bagging ensembles.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2007

Out of Bootstrap Estimation of Generalization Error Curves in Bagging Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Data Engineering and Automated Learning, 2007

Selection of Decision Stumps in Bagging Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2007

GARCH Processes with Non-parametric Innovations for Market Risk Estimation.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2007

Use of heuristic rules in evolutionary methods for the selection of optimal investment portfolios.

[BibT_eX]

[DOI]

Proceedings of the IEEE Congress on Evolutionary Computation, 2007

2006

Pruning in Ordered Regression Bagging Ensembles.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2006

Evaluation of Decision Tree Pruning with Subadditive Penalties.

[BibT_eX]

[DOI]

Sergio García-Moratilla

Proceedings of the Intelligent Data Engineering and Automated Learning, 2006

Pruning in ordered bagging ensembles.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2006

Building Ensembles of Neural Networks with Class-Switching.

[BibT_eX]

[DOI]

Aitor Sánchez-Martínez

Proceedings of the Artificial Neural Networks, 2006

Competitive and Collaborative Mixtures of Experts for Financial Risk Analysis.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2006

Selection of Optimal Investment Portfolios with Cardinality Constraints.

[BibT_eX]

[DOI]

Rafael Moral-Escudero

Proceedings of the IEEE International Conference on Evolutionary Computation, 2006

2005

Switching class labels to generate classification ensembles.

[BibT_eX]

[DOI]

Pattern Recognit., 2005

2004

Using all data to generate decision tree ensembles.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Part C, 2004

2003

Hierarchical Mixtures of Autoregressive Models for Time-Series Modeling.

[BibT_eX]

[DOI]

Carmen Vidal

Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003

Cellular Automata and Probabilistic L Systems: An Example in Ecology.

[BibT_eX]

Manuel Alfonseca

Alfonso Ortega

Proceedings of the Grammars and Automata for String Processing: From Mathematics and Computer Science to Biology, 2003

2002

Mixtures of Autoregressive Models for Financial Risk Analysis.

[BibT_eX]

[DOI]

Francisco de Borja Rodríguez Ortiz

Proceedings of the Artificial Neural Networks, 2002

2001

Period Focusing Induced by Network Feedback in Populations of Noisy Integrate-and-Fire Neurons.

[BibT_eX]

[DOI]

Vicente López

Neural Comput., 2001

e-Portfolio: Java Technology for Financial Applications on the Internet.

[BibT_eX]

Pablo Castells

Proceedings of WebNet 2001, 2001

Backpropagation in Decision Trees for Regression.

[BibT_eX]

[DOI]

Victor Medina-Chico

James F. Lutsko

Proceedings of the Machine Learning: EMCL 2001, 2001

1999

Globally Optimal Fuzzy Decision Trees for Classification and Regression.

[BibT_eX]

[DOI]