High-order Boltzmann machines applied to the Monk's problems. - Manuel Graña; Víctor Lavín Puente; Alicia D'Anjou; Francisco X. Albizuri; José Antonio Lozano 001 (ESANN, 1994)

Convergence Properties of High-order Boltzmann Machines. - F. Xabier Albizuri; Alicia D'Anjou; Manuel Graña; José Antonio Lozano 001 (Neural Networks, 1996)

Experimental Results of a Michigan-like Evolution Strategy for Non-stationary Clustering. - Ana Isabel González; Manuel Graña; José Antonio Lozano 001; Pedro Larrañaga (ICANNGA, 1997)

Aplicación de los algoritmos genéticos al problema del clustering jerárquico. - José Antonio Lozano 001; Pedro Larrañaga (Inteligencia Artif., 1998)

Representing the behaviour of supervised classification learning algorithms by Bayesian networks. - Iñaki Inza; Pedro Larrañaga; Basilio Sierra; Ramon Etxeberria; José Antonio Lozano 001; José M. Peña 001 (Pattern Recognit. Lett., 1999)

Applying genetic algorithms to search for the best hierarchical clustering of a dataset. - José Antonio Lozano 001; Pedro Larrañaga (Pattern Recognit. Lett., 1999)

An empirical comparison of four initialization methods for the K-Means algorithm. - José M. Peña 001; José Antonio Lozano 001; Pedro Larrañaga (Pattern Recognit. Lett., 1999)

Learning Bayesian networks for clustering by means of constructive induction. - José M. Peña 001; José Antonio Lozano 001; Pedro Larrañaga (Pattern Recognit. Lett., 1999)

Genetic Algorithms: Bridging the Convergence Gap. - José Antonio Lozano 001; Pedro Larrañaga; Manuel Graña; F. Xabier Albizuri (Theor. Comput. Sci., 1999)

Combinatonal Optimization by Learning and Simulation of Bayesian Networks. - Pedro Larrañaga; Ramon Etxeberria; José Antonio Lozano 001; José M. Peña 001 (UAI, 2000)

Analyzing the Population Based Incremental Learning Algorithm by Means of Discrete Dynamical Systems. - Cristina González; José Antonio Lozano 001; Pedro Larrañaga (Complex Syst., 2000)

An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering. - José M. Peña 001; José Antonio Lozano 001; Pedro Larrañaga (Pattern Recognit. Lett., 2000)

Geographical clustering of cancer incidence by means of Bayesian networks and conditional Gaussian networks. - José M. Peña 001; I. Izarzugaza; José Antonio Lozano 001; E. Aldasoro; Pedro Larrañaga (AISTATS, 2001)

Performance evaluation of compromise conditional Gaussian networks for data clustering. - José M. Peña 001; José Antonio Lozano 001; Pedro Larrañaga (Int. J. Approx. Reason., 2001)

Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks. - José M. Peña 001; José Antonio Lozano 001; Pedro Larrañaga; Iñaki Inza (IEEE Trans. Pattern Anal. Mach. Intell., 2001)

Experimental Results in Function Optimization with EDAs in Continuous Domain. - Endika Bengoetxea; Teresa Miquélez; Pedro Larrañaga; José Antonio Lozano 001 (Estimation of Distribution Algorithms, 2002)

An Empirical Comparison of Discrete Estimation of Distribution Algorithms. - Rosa Blanco; José Antonio Lozano 001 (Estimation of Distribution Algorithms, 2002)

Mathematical Modeling of Discrete Estimation of Distribution Algorithms. - Cristina González; José Antonio Lozano 001; Pedro Larrañaga (Estimation of Distribution Algorithms, 2002)

An Introduction to Evolutionary Algorithms. - José Antonio Lozano 001 (Estimation of Distribution Algorithms, 2002)

Estimation of Distribution Algorithms Applied to the Job Shop Scheduling Problem: Some Preliminary Research. - José Antonio Lozano 001; Alexander Mendiburu (Estimation of Distribution Algorithms, 2002)

Parallel Estimation of Distribution Algorithms. - José Antonio Lozano 001; Ramón Sagarna; Pedro Larrañaga (Estimation of Distribution Algorithms, 2002)

Benefits of Data Clustering in Multimodal Function Optimization via EDAs. - José M. Peña 001; José Antonio Lozano 001; Pedro Larrañaga (Estimation of Distribution Algorithms, 2002)

Unsupervised Learning of Bayesian Networks Via Estimation of Distribution Algorithms. - José M. Peña 001; José Antonio Lozano 001; Pedro Larrañaga (Probabilistic Graphical Models, 2002)

Mathematical modelling of UMDAc algorithm with tournament selection. Behaviour on linear and quadratic functions. - Cristina González; José Antonio Lozano 001; Pedro Larrañaga (Int. J. Approx. Reason., 2002)

Synergies between evolutionary computation and probabilistic graphical models. - Pedro Larrañaga; José Antonio Lozano 001 (Int. J. Approx. Reason., 2002)

Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction. - José M. Peña 001; José Antonio Lozano 001; Pedro Larrañaga (Mach. Learn., 2002)

Analysis of the Univariate Marginal Distribution Algorithm Modeled by Markov Chains. - Cristina González; Juan Diego Rodríguez; José Antonio Lozano 001; Pedro Larrañaga (IWANN (1), 2003)

Algoritmos de Estimación de Distribuciones en Problemas de Optimización Combinatoria. - Pedro Larrañaga; José Antonio Lozano 001; Heinz Mühlenbein (Inteligencia Artif., 2003)

Protein Folding in 2-Dimensional Lattices with Estimation of Distribution Algorithms. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (ISBMDA, 2004)

Unsupervised Learning Of Bayesian Networks Via Estimation Of Distribution Algorithms: An Application To Gene Expression Data Clustering. - José M. Peña 001; José Antonio Lozano 001; Pedro Larrañaga (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2004)

A multiobjective approach to the portfolio optimization problem. - Rubén Armañanzas; José Antonio Lozano 001 (Congress on Evolutionary Computation, 2005)

Interactions and dependencies in estimation of distribution algorithms. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (Congress on Evolutionary Computation, 2005)

Discriminative Learning of Bayesian Network Classifiers via the TM Algorithm. - Guzmán Santafé; José Antonio Lozano 001; Pedro Larrañaga (ECSQARU, 2005)

Parallel and Multi-Objective EDAs to Create Multivariate Calibration Models for Quantitative Chemical Applications. - Alexander Mendiburu; José Miguel-Alonso; José Antonio Lozano 001; Miren Ostra; Carlos Ubide (ICPP Workshops, 2005)

Average Time Complexity of Estimation of Distribution Algorithms. - Cristina González; A. Ramírez; José Antonio Lozano 001; Pedro Larrañaga (IWANN, 2005)

On The Performance Of Estimation Of Distribution Algorithms Applied To Software Testing. - Ramón Sagarna; José Antonio Lozano 001 (Appl. Artif. Intell., 2005)

Editorial Introduction Special Issue on Estimation of Distribution Algorithms. - Pedro Larrañaga; José Antonio Lozano 001 (Evol. Comput., 2005)

Globally Multimodal Problem Optimization Via an Estimation of Distribution Algorithm Based on Unsupervised Learning of Bayesian Networks. - José M. Peña 001; José Antonio Lozano 001; Pedro Larrañaga (Evol. Comput., 2005)

Editorial. - Pedro Larrañaga; José Antonio Lozano 001; José M. Peña 001; Iñaki Inza (Mach. Learn., 2005)

Parallel Implementation of EDAs Based on Probabilistic Graphical Models. - Alexander Mendiburu; José Antonio Lozano 001; José Miguel-Alonso (IEEE Trans. Evol. Comput., 2005)

Evaluation of Parallel EDAs to Create Chemical Calibration Models. - Alexander Mendiburu; José Miguel-Alonso; José Antonio Lozano 001 (e-Science, 2006)

Mixtures of Kikuchi Approximations. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (ECML, 2006)

Bayesian Model Averaging of TAN Models for Clustering. - Guzmán Santafé; José Antonio Lozano 001; Pedro Larrañaga (Probabilistic Graphical Models, 2006)

Discriminative Learning of Bayesian Network Classifiers. - Guzmán Santafé; José Antonio Lozano 001; Pedro Larrañaga (Inteligencia Artif., 2006)

Machine learning in bioinformatics. - Pedro Larrañaga; Borja Calvo; Roberto Santana 001; Concha Bielza; Josu Galdiano; Iñaki Inza; José Antonio Lozano 001; Rubén Armañanzas; Guzmán Santafé; Aritz Pérez Martínez; Victor Robles (Briefings Bioinform., 2006)

Scatter Search in software testing, comparison and collaboration with Estimation of Distribution Algorithms. - Ramón Sagarna; José Antonio Lozano 001 (Eur. J. Oper. Res., 2006)

Parallel EDAs to create multivariate calibration models for quantitative chemical applications. - Alexander Mendiburu; José Miguel-Alonso; José Antonio Lozano 001; Miren Ostra; Carlos Ubide (J. Parallel Distributed Comput., 2006)

Implementation and Performance Evaluation of a Parallelization of Estimation of Bayesian Network Algorithms. - Alexander Mendiburu; José Miguel-Alonso; José Antonio Lozano 001 (Parallel Process. Lett., 2006)

Bayesian Model Averaging of Naive Bayes for Clustering. - Guzmán Santafé; José Antonio Lozano 001; Pedro Larrañaga (IEEE Trans. Syst. Man Cybern. Part B, 2006)

Exact Bayesian network learning in estimation of distribution algorithms. - Carlos Echegoyen; José Antonio Lozano 001; Roberto Santana 001; Pedro Larrañaga (IEEE Congress on Evolutionary Computation, 2007)

Discriminative vs. Generative Learning of Bayesian Network Classifiers. - Guzmán Santafé; José Antonio Lozano 001; Pedro Larrañaga (ECSQARU, 2007)

The Role of a Priori Information in the Minimization of Contact Potentials by Means of Estimation of Distribution Algorithms. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (EvoBIO, 2007)

A parallel framework for loopy belief propagation. - Alexander Mendiburu; Roberto Santana 001; José Antonio Lozano 001; Endika Bengoetxea (GECCO (Companion), 2007)

Side chain placement using estimation of distribution algorithms. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (Artif. Intell. Medicine, 2007)

A partially supervised classification approach to dominant and recessive human disease gene prediction. - Borja Calvo; Núria López-Bigas; Simon J. Furney; Pedro Larrañaga; José Antonio Lozano 001 (Comput. Methods Programs Biomed., 2007)

Learning Bayesian classifiers from positive and unlabeled examples. - Borja Calvo; Pedro Larrañaga; José Antonio Lozano 001 (Pattern Recognit. Lett., 2007)

A multi-objective approach to the Channel Assignment Problem. - Jayrani Cheeneebash; José Antonio Lozano 001; Harry C. S. Rughooputh (IEEE Congress on Evolutionary Computation, 2008)

Component weighting functions for adaptive search with EDAs. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (IEEE Congress on Evolutionary Computation, 2008)

Multi-Objective Learning of Multi-Dimensional Bayesian Classifiers. - Juan Diego Rodríguez; José Antonio Lozano 001 (HIS, 2008)

Adding Probabilistic Dependencies to the Search of Protein Side Chain Configurations Using EDAs. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (PPSN, 2008)

A review of estimation of distribution algorithms in bioinformatics. - Rubén Armañanzas; Iñaki Inza; Roberto Santana 001; Yvan Saeys; Jose Luis Flores 001; José Antonio Lozano 001; Yves Van de Peer; Rosa Blanco; Víctor Robles; Concha Bielza; Pedro Larrañaga (BioData Min., 2008)

Dynamic Search Space Transformations for Software Test Data Generation. - Ramón Sagarna; José Antonio Lozano 001 (Comput. Intell., 2008)

Combining variable neighborhood search and estimation of distribution algorithms in the protein side chain placement problem. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (J. Heuristics, 2008)

Inference of Population Structure Using Genetic Markers and a Bayesian Model Averaging Approach for Clustering. - Guzmán Santafé; José Antonio Lozano 001; Pedro Larrañaga (J. Comput. Biol., 2008)

Protein Folding in Simplified Models With Estimation of Distribution Algorithms. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (IEEE Trans. Evol. Comput., 2008)

The Impact of Exact Probabilistic Learning Algorithms in EDAs Based on Bayesian Networks. - Carlos Echegoyen; Roberto Santana 001; José Antonio Lozano 001; Pedro Larrañaga (Linkage in Evolutionary Computation, 2008)

Adaptive Estimation of Distribution Algorithms. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (Adaptive and Multilevel Metaheuristics, 2008)

Analyzing the probability of the optimum in EDAs based on Bayesian networks. - Carlos Echegoyen; Alexander Mendiburu; Roberto Santana 001; José Antonio Lozano 001 (IEEE Congress on Evolutionary Computation, 2009)

A new preprocessing procedure for the haplotype inference problem. - Ekhine Irurozki; José Antonio Lozano 001 (IEEE Congress on Evolutionary Computation, 2009)

Mining probabilistic models learned by EDAs in the optimization of multi-objective problems. - Roberto Santana 001; Concha Bielza; José Antonio Lozano 001; Pedro Larrañaga (GECCO, 2009)

Research topics in discrete estimation of distribution algorithms based on factorizations. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (Memetic Comput., 2009)

Feature subset selection from positive and unlabelled examples. - Borja Calvo; Pedro Larrañaga; José Antonio Lozano 001 (Pattern Recognit. Lett., 2009)

Guest Editorial: Special Issue on Evolutionary Algorithms Based on Probabilistic Models. - José Antonio Lozano 001; Qingfu Zhang 001; Pedro Larrañaga (IEEE Trans. Evol. Comput., 2009)

Estimation of Bayesian networks algorithms in a class of complex networks. - Carlos Echegoyen; Alexander Mendiburu; Roberto Santana 001; José Antonio Lozano 001 (IEEE Congress on Evolutionary Computation, 2010)

Strategies to Map Parallel Applications onto Meshes. - Jose Antonio Pascual; José Miguel-Alonso; José Antonio Lozano 001 (DCAI, 2010)

Multi-marker tagging single nucleotide polymorphism selection using estimation of distribution algorithms. - Roberto Santana 001; Alexander Mendiburu; Noah Zaitlen; Eleazar Eskin; José Antonio Lozano 001 (Artif. Intell. Medicine, 2010)

Learning Factorizations in Estimation of Distribution Algorithms Using Affinity Propagation. - Roberto Santana 001; Pedro Larrañaga; José Antonio Lozano 001 (Evol. Comput., 2010)

Sensitivity Analysis of k-Fold Cross Validation in Prediction Error Estimation. - Juan Diego Rodríguez; Aritz Pérez Martínez; José Antonio Lozano 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2010)

A Review on Parallel Estimation of Distribution Algorithms. - Alexander Mendiburu; José Miguel-Alonso; José Antonio Lozano 001 (Parallel and Distributed Computational Intelligence, 2010)

Learning Probability Distributions over Permutations by Means of Fourier Coefficients. - Ekhine Irurozki; Borja Calvo; José Antonio Lozano 001 (Canadian AI, 2011)

On the limits of effectiveness in estimation of distribution algorithms. - Carlos Echegoyen; Qingfu Zhang 001; Alexander Mendiburu; Roberto Santana 001; José Antonio Lozano 001 (IEEE Congress on Evolutionary Computation, 2011)

A study on the complexity of TSP instances under the 2-exchange neighbor system. - Leticia Hernando; Jose Antonio Pascual; Alexander Mendiburu; José Antonio Lozano 001 (FOCI, 2011)

A preliminary study on EDAs for permutation problems based on marginal-based models. - Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (GECCO, 2011)

Introducing the Mallows Model on Estimation of Distribution Algorithms. - Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (ICONIP (2), 2011)

Optimization-based mapping framework for parallel applications. - Jose Antonio Pascual; José Miguel-Alonso; José Antonio Lozano 001 (J. Parallel Distributed Comput., 2011)

A Preprocessing Procedure for Haplotype Inference by Pure Parsimony. - Ekhine Irurozki; Borja Calvo; José Antonio Lozano 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

Structural transfer using EDAs: An application to multi-marker tagging SNP selection. - Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (IEEE Congress on Evolutionary Computation, 2012)

An analysis of the use of probabilistic modeling for synaptic connectivity prediction from genomic data. - Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (IEEE Congress on Evolutionary Computation, 2012)

Evolving NK-complexity for evolutionary solvers. - Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (GECCO (Companion), 2012)

An interactive optimization approach to a real-world oceanographic campaign planning problem. - Izaskun Ibarbia; Alexander Mendiburu; Maria Santos 001; José Antonio Lozano 001 (Appl. Intell., 2012)

A Markovianity based optimisation algorithm. - Siddhartha Shakya; Roberto Santana 001; José Antonio Lozano 001 (Genet. Program. Evolvable Mach., 2012)

Approaching Sentiment Analysis by using semi-supervised learning of multi-dimensional classifiers. - Jonathan Ortigosa-Hernández; Juan Diego Rodríguez; Leandro Alzate; Manuel Lucania; Iñaki Inza; José Antonio Lozano 001 (Neurocomputing, 2012)

Wrapper positive Bayesian network classifiers. - Borja Calvo; Iñaki Inza; Pedro Larrañaga; José Antonio Lozano 001 (Knowl. Inf. Syst., 2012)

A review on estimation of distribution algorithms in permutation-based combinatorial optimization problems. - Josu Ceberio; Ekhine Irurozki; Alexander Mendiburu; José Antonio Lozano 001 (Prog. Artif. Intell., 2012)

Toward Understanding EDAs Based on Bayesian Networks Through a Quantitative Analysis. - Carlos Echegoyen; Alexander Mendiburu; Roberto Santana 001; José Antonio Lozano 001 (IEEE Trans. Evol. Comput., 2012)

Using Multidimensional Bayesian Network Classifiers to Assist the Treatment of Multiple Sclerosis. - Juan Diego Rodríguez; Aritz Pérez Martínez; David Arteta; Diego Tejedor; José Antonio Lozano 001 (IEEE Trans. Syst. Man Cybern. Part C, 2012)

Learning from Crowds in Multi-dimensional Classification Domains. - Jerónimo Hernández-González; Iñaki Inza; José Antonio Lozano 001 (CAEPIA, 2013)

Multidimensional k-Interaction Classifier: Taking Advantage of All the Information Contained in Low Order Interactions. - Aritz Pérez Martínez; José Antonio Lozano 001; Iñaki Inza (CAEPIA, 2013)

The Plackett-Luce ranking model on permutation-based optimization problems. - Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (IEEE Congress on Evolutionary Computation, 2013)

Symmetry in evolutionary and estimation of distribution algorithms. - Roberto Santana 001; Robert I. McKay; José Antonio Lozano 001 (IEEE Congress on Evolutionary Computation, 2013)

Understanding Instance Complexity in the Linear Ordering Problem. - Josu Ceberio; Leticia Hernando; Alexander Mendiburu; José Antonio Lozano 001 (IDEAL, 2013)

Generating Customized Landscapes in Permutation-Based Combinatorial Optimization Problems. - Leticia Hernando; Alexander Mendiburu; José Antonio Lozano 001 (LION, 2013)

Critical Issues in Model-Based Surrogate Functions in Estimation of Distribution Algorithms. - Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (SEMCCO (2), 2013)

Message Passing Methods for Estimation of Distribution Algorithms Based on Markov Networks. - Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (SEMCCO (2), 2013)

Combinatorial Optimization by Learning and Simulation of Bayesian Networks - Pedro Larrañaga; Ramon Etxeberria; José Antonio Lozano 001; José M. Peña 001 (CoRR, 2013)

On the Taxonomy of Optimization Problems Under Estimation of Distribution Algorithms. - Carlos Echegoyen; Alexander Mendiburu; Roberto Santana 001; José Antonio Lozano 001 (Evol. Comput., 2013)

An Evaluation of Methods for Estimating the Number of Local Optima in Combinatorial Optimization Problems. - Leticia Hernando; Alexander Mendiburu; José Antonio Lozano 001 (Evol. Comput., 2013)

Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting. - Jose A. Fernandes; José Antonio Lozano 001; Iñaki Inza; Xabier Irigoien; Aritz Pérez; Juan Diego Rodríguez (Environ. Model. Softw., 2013)

Significance tests or confidence intervals: which are preferable for the comparison of classifiers? - Daniel P. Berrar; José Antonio Lozano 001 (J. Exp. Theor. Artif. Intell., 2013)

Learning Bayesian network classifiers from label proportions. - Jerónimo Hernández-González; Iñaki Inza; José Antonio Lozano 001 (Pattern Recognit., 2013)

A general framework for the statistical analysis of the sources of variance for classification error estimators. - Juan Diego Rodríguez; Aritz Pérez Martínez; José Antonio Lozano 001 (Pattern Recognit., 2013)

Extending distance-based ranking models in estimation of distribution algorithms. - Josu Ceberio; Ekhine Irurozki; Alexander Mendiburu; José Antonio Lozano 001 (IEEE Congress on Evolutionary Computation, 2014)

Estimation of Distribution Algorithms based Unmanned Aerial Vehicle path planner using a new coordinate system. - Peng Yang 008; Ke Tang 001; José Antonio Lozano 001 (IEEE Congress on Evolutionary Computation, 2014)

Optimization of Application Placement Towards a Greener Cloud Infrastructure. - Tania Lorido-Botran; Jose Antonio Pascual; José Miguel-Alonso; José Antonio Lozano 001 (EvoApplications, 2014)

Iterative Probabilistic Tree Search for the Minimum Common String Partition Problem. - Christian Blum 001; José Antonio Lozano 001; Pedro Pinacho Davidson (Hybrid Metaheuristics, 2014)

Learning Maximum Weighted (k+1)-Order Decomposable Graphs by Integer Linear Programming. - Aritz Pérez; Christian Blum 001; José Antonio Lozano 001 (Probabilistic Graphical Models, 2014)

Customized Selection in Estimation of Distribution Algorithms. - Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (SEAL, 2014)

A fast implementation of the first fit contiguous partitioning strategy for cubic topologies. - Jose Antonio Pascual; José Miguel-Alonso; José Antonio Lozano 001 (Concurr. Comput. Pract. Exp., 2014)

A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments. - Tania Lorido-Botran; José Miguel-Alonso; José Antonio Lozano 001 (J. Grid Comput., 2014)

Assisting in search heuristics selection through multidimensional supervised classification: A case study on software testing. - Ramón Sagarna; Alexander Mendiburu; Iñaki Inza; José Antonio Lozano 001 (Inf. Sci., 2014)

Application-aware metrics for partition selection in cube-shaped topologies. - Jose Antonio Pascual; José Miguel-Alonso; José Antonio Lozano 001 (Parallel Comput., 2014)

A Distance-Based Ranking Model Estimation of Distribution Algorithm for the Flowshop Scheduling Problem. - Josu Ceberio; Ekhine Irurozki; Alexander Mendiburu; José Antonio Lozano 001 (IEEE Trans. Evol. Comput., 2014)

Multi-objectivising the Quadratic Assignment Problem by Means of an Elementary Landscape Decomposition. - Josu Ceberio; Borja Calvo; Alexander Mendiburu; José Antonio Lozano 001 (CAEPIA, 2015)

A Novel Weakly Supervised Problem: Learning from Positive-Unlabeled Proportions. - Jerónimo Hernández-González; Iñaki Inza; José Antonio Lozano 001 (CAEPIA, 2015)

Mixtures of Generalized Mallows models for solving the quadratic assignment problem. - Josu Ceberio; Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (CEC, 2015)

Evolving MNK-landscapes with structural constraints. - Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (CEC, 2015)

Kernels of Mallows Models for Solving Permutation-based Problems. - Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (GECCO, 2015)

Multi-objective NM-Landscapes. - Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (GECCO (Companion), 2015)

Dealing with the evaluation of supervised classification algorithms. - Guzmán Santafé; Iñaki Inza; José Antonio Lozano 001 (Artif. Intell. Rev., 2015)

An Artificial Bioindicator System for Network Intrusion Detection. - Christian Blum 001; José Antonio Lozano 001; Pedro Pinacho Davidson (Artif. Life, 2015)

Multi-view classification of psychiatric conditions based on saccades. - Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (Appl. Soft Comput., 2015)

A review of distances for the Mallows and Generalized Mallows estimation of distribution algorithms. - Josu Ceberio; Ekhine Irurozki; Alexander Mendiburu; José Antonio Lozano 001 (Comput. Optim. Appl., 2015)

Computing factorized approximations of Pareto-fronts using mNM-landscapes and Boltzmann distributions. - Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (CoRR, 2015)

Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species. - Jose A. Fernandes; Xabier Irigoien; José Antonio Lozano 001; Iñaki Inza; Nerea Goikoetxea; Aritz Pérez Martínez (Ecol. Informatics, 2015)

Mathematical programming strategies for solving the minimum common string partition problem. - Christian Blum 001; José Antonio Lozano 001; Pedro Pinacho Davidson (Eur. J. Oper. Res., 2015)

The linear ordering problem revisited. - Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (Eur. J. Oper. Res., 2015)

Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies. - Jose Antonio Pascual; Tania Lorido-Botran; José Miguel-Alonso; José Antonio Lozano 001 (J. Grid Comput., 2015)

Multidimensional Learning from Crowds: Usefulness and Application of Expertise Detection. - Jerónimo Hernández-González; Iñaki Inza; José Antonio Lozano 001 (Int. J. Intell. Syst., 2015)

Gene-Gene Interactions Detection Using a Two-stage Model. - Zhanyong Wang; Jae Hoon Sul; Sagi Snir; José Antonio Lozano 001; Eleazar Eskin (J. Comput. Biol., 2015)

Comprehensive characterization of the behaviors of estimation of distribution algorithms. - Carlos Echegoyen; Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (Theor. Comput. Sci., 2015)

A Boltzmann-Based Estimation of Distribution Algorithm for a General Resource Scheduling Model. - Xinle Liang; Huaping Chen 001; José Antonio Lozano 001 (IEEE Trans. Evol. Comput., 2015)

Locality-aware policies to improve job scheduling on 3D tori. - Jose Antonio Pascual; José Miguel-Alonso; José Antonio Lozano 001 (J. Supercomput., 2015)

Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints. - Peng Yang 008; Ke Tang 001; José Antonio Lozano 001; Xianbin Cao 001 (IEEE Trans. Robotics, 2015)

A Note on the Boltzmann Distribution and the Linear Ordering Problem. - Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (CAEPIA, 2016)

Estimating Attraction Basin Sizes. - Leticia Hernando; Alexander Mendiburu; José Antonio Lozano 001 (CAEPIA, 2016)

Bayesian optimization for parameter tuning in evolutionary algorithms. - Ibai Roman; Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (CEC, 2016)

Analyzing the Performance of Allocation Strategies Based on Space-Filling Curves. - Jose Antonio Pascual; José Antonio Lozano 001; José Miguel-Alonso (JSSPP, 2016)

Construct, Merge, Solve & Adapt A new general algorithm for combinatorial optimization. - Christian Blum 001; Pedro Pinacho Davidson; Manuel López-Ibáñez 001; José Antonio Lozano 001 (Comput. Oper. Res., 2016)

An efficient K-means algorithm for Massive Data. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (CoRR, 2016)

Efficient approximation of probability distributions with k-order decomposable models. - Aritz Pérez; Iñaki Inza; José Antonio Lozano 001 (Int. J. Approx. Reason., 2016)

A review of message passing algorithms in estimation of distribution algorithms. - Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (Nat. Comput., 2016)

Vine copula classifiers for the mind reading problem. - Diana Carrera; Roberto Santana 001; José Antonio Lozano 001 (Prog. Artif. Intell., 2016)

Weak supervision and other non-standard classification problems: A taxonomy. - Jerónimo Hernández-González; Iñaki Inza; José Antonio Lozano 001 (Pattern Recognit. Lett., 2016)

Distance Measures for Time Series in R: The TSdist Package. - Usue Mori; Alexander Mendiburu; José Antonio Lozano 001 (R J., 2016)

A Tunable Generator of Instances of Permutation-Based Combinatorial Optimization Problems. - Leticia Hernando; Alexander Mendiburu; José Antonio Lozano 001 (IEEE Trans. Evol. Comput., 2016)

A Sparse Spectral Clustering Framework via Multiobjective Evolutionary Algorithm. - Juanjuan Luo; Licheng Jiao; José Antonio Lozano 001 (IEEE Trans. Evol. Comput., 2016)

Estimation of the Distribution Algorithm With a Stochastic Local Search for Uncertain Capacitated Arc Routing Problems. - Juan Wang; Ke Tang 001; José Antonio Lozano 001; Xin Yao 001 (IEEE Trans. Evol. Comput., 2016)

Similarity Measure Selection for Clustering Time Series Databases. - Usue Mori; Alexander Mendiburu; José Antonio Lozano 001 (IEEE Trans. Knowl. Data Eng., 2016)

Semisupervised Multiclass Classification Problems With Scarcity of Labeled Data: A Theoretical Study. - Jonathan Ortigosa-Hernández; Iñaki Inza; José Antonio Lozano 001 (IEEE Trans. Neural Networks Learn. Syst., 2016)

Combining CMA-ES and MOEA/DD for many-objective optimization. - Olacir R. Castro Jr.; Roberto Santana 001; José Antonio Lozano 001; Aurora T. R. Pozo (CEC, 2017)

A square lattice probability model for optimising the Graph Partitioning Problem. - Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (CEC, 2017)

Are we generating instances uniformly at random? - Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (CEC, 2017)

General chair's welcome. - José Antonio Lozano 001 (CEC, 2017)

Nature-inspired approaches for distance metric learning in multivariate time series classification. - Izaskun Oregi; Javier Del Ser; Aritz Pérez; José Antonio Lozano 001 (CEC, 2017)

Evolutionary algorithms to optimize low-thrust trajectory design in spacecraft orbital precession mission. - Abolfazl Shirazi; Josu Ceberio; José Antonio Lozano 001 (CEC, 2017)

The Weighted Independent Domination Problem: ILP Model and Algorithmic Approaches. - Pedro Pinacho Davidson; Christian Blum 001; José Antonio Lozano 001 (EvoCOP, 2017)

Different scenarios for survival analysis of evolutionary algorithms. - Roberto Santana 001; José Antonio Lozano 001 (GECCO, 2017)

On-Line Dynamic Time Warping for Streaming Time Series. - Izaskun Oregi; Aritz Pérez; Javier Del Ser; José Antonio Lozano 001 (ECML/PKDD (2), 2017)

Conference Report on 2017 IEEE Congress on Evolutionary Computation (IEEE CEC 2017) [Conference Reports]. - José Antonio Lozano 001 (IEEE Comput. Intell. Mag., 2017)

Reliable early classification of time series based on discriminating the classes over time. - Usue Mori; Alexander Mendiburu; Eamonn J. Keogh; José Antonio Lozano 001 (Data Min. Knowl. Discov., 2017)

Learning from Proportions of Positive and Unlabeled Examples. - Jerónimo Hernández-González; Iñaki Inza; José Antonio Lozano 001 (Int. J. Intell. Syst., 2017)

An efficient approximation to the K-means clustering for massive data. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (Knowl. Based Syst., 2017)

Transfer weight functions for injecting problem information in the multi-objective CMA-ES. - Olacir R. Castro Jr.; Aurora T. R. Pozo; José Antonio Lozano 001; Roberto Santana 001 (Memetic Comput., 2017)

Measuring the class-imbalance extent of multi-class problems. - Jonathan Ortigosa-Hernández; Iñaki Inza; José Antonio Lozano 001 (Pattern Recognit. Lett., 2017)

An investigation of clustering strategies in many-objective optimization: the I-Multi algorithm as a case study. - Olacir R. Castro Jr.; Aurora T. R. Pozo; José Antonio Lozano 001; Roberto Santana 001 (Swarm Intell., 2017)

Editorial: A Successful Year and Looking Forward to 2017 and Beyond. - Haibo He; Robert Haas; Jun Fu; Barbara Hammer; Daniel W. C. Ho; Fakhri Karray; Dhireesha Kudithipudi; José Antonio Lozano 001; Teresa Bernarda Ludermir; Jacek Mandziuk; Stefano Melacci; Antonio Paiva; et al. (IEEE Trans. Neural Networks Learn. Syst., 2017)

Distance-Based Exponential Probability Models for Constrained Combinatorial Problems. - Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (CAEPIA, 2018)

Hill-Climbing Algorithm: Let's Go for a Walk Before Finding the Optimum. - Leticia Hernando; Alexander Mendiburu; José Antonio Lozano 001 (CEC, 2018)

Are the Artificially Generated Instances Uniform in Terms of Difficulty? - Aritz Pérez; Josu Ceberio; José Antonio Lozano 001 (CEC, 2018)

Bayesian inference for algorithm ranking analysis. - Borja Calvo; Josu Ceberio; José Antonio Lozano 001 (GECCO (Companion), 2018)

Distance-based exponential probability models on constrained combinatorial optimization problems. - Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (GECCO (Companion), 2018)

Adversarial Sample Crafting for Time Series Classification with Elastic Similarity Measures. - Izaskun Oregi; Javier Del Ser; Aritz Pérez; José Antonio Lozano 001 (IDC, 2018)

The Relationship Between Graphical Representations of Regular Vine Copulas and Polytrees. - Diana Carrera; Roberto Santana 001; José Antonio Lozano 001 (IPMU (3), 2018)

Approximating the maximum weighted decomposable graph problem with applications to probabilistic graphical models. - Aritz Pérez; Christian Blum 001; José Antonio Lozano 001 (PGM, 2018)

Learning to classify software defects from crowds: A novel approach. - Jerónimo Hernández-González; Daniel Rodríguez 001; Iñaki Inza; Rachel Harrison; José Antonio Lozano 001 (Appl. Soft Comput., 2018)

An efficient evolutionary algorithm for the orienteering problem. - Gorka Kobeaga; María Merino 001; José Antonio Lozano 001 (Comput. Oper. Res., 2018)

An efficient K -means clustering algorithm for massive data. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (CoRR, 2018)

Merge Non-Dominated Sorting Algorithm for Many-Objective Optimization. - Javier Moreno 004; Daniel Rodríguez 001; Antonio J. Nebro; José Antonio Lozano 001 (CoRR, 2018)

A system for airport weather forecasting based on circular regression trees. - Pablo Rozas Larraondo; Iñaki Inza; José Antonio Lozano 001 (Environ. Model. Softw., 2018)

The weighted independent domination problem: Integer linear programming models and metaheuristic approaches. - Pedro Pinacho Davidson; Christian Blum 001; José Antonio Lozano 001 (Eur. J. Oper. Res., 2018)

Effects of Reducing VMs Management Times on Elastic Applications. - Jose Antonio Pascual; José Antonio Lozano 001; José Miguel-Alonso (J. Grid Comput., 2018)

Estimating attraction basin sizes of combinatorial optimization problems. - Anne Elorza; Leticia Hernando; Alexander Mendiburu; José Antonio Lozano 001 (Prog. Artif. Intell., 2018)

Early Classification of Time Series by Simultaneously Optimizing the Accuracy and Earliness. - Usue Mori; Alexander Mendiburu; Sanjoy Dasgupta; José Antonio Lozano 001 (IEEE Trans. Neural Networks Learn. Syst., 2018)

Multi-start Methods. - Rafael Martí; José Antonio Lozano 001; Alexander Mendiburu; Leticia Hernando (Handbook of Heuristics, 2018)

Hybrid Heuristics for the Linear Ordering Problem. - Erik Garcia; Josu Ceberio; José Antonio Lozano 001 (CEC, 2019)

Bayesian performance analysis for black-box optimization benchmarking. - Borja Calvo; Ofer M. Shir; Josu Ceberio; Carola Doerr; Hao Wang 025; Thomas Bäck; José Antonio Lozano 001 (GECCO (Companion), 2019)

Characterising the rankings produced by combinatorial optimisation problems and finding their intersections. - Leticia Hernando; Alexander Mendiburu; José Antonio Lozano 001 (GECCO, 2019)

Sentiment analysis with genetically evolved gaussian kernels. - Ibai Roman; Alexander Mendiburu; Roberto Santana 001; José Antonio Lozano 001 (GECCO, 2019)

Bayesian Optimization Approaches for Massively Multi-modal Problems. - Ibai Roman; Alexander Mendiburu; Roberto Santana 001; José Antonio Lozano 001 (LION, 2019)

Evolving Gaussian Process Kernels for Translation Editing Effort Estimation. - Ibai Roman; Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (LION, 2019)

Data generation approaches for topic classification in multilingual spoken dialog systems. - César Montenegro; Roberto Santana 001; José Antonio Lozano 001 (PETRA, 2019)

The EMPATHIC project: mid-term achievements. - María Inés Torres; Javier Mikel Olaso; César Montenegro; Roberto Santana 001; Alain Vázquez; Raquel Justo; José Antonio Lozano 001; Stephan Schlögl; Gérard Chollet; Nazim Dugan; M. Irvine; Neil Glackin; et al. (PETRA, 2019)

An Experimental Study in Adaptive Kernel Selection for Bayesian Optimization. - Ibai Roman; Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (IEEE Access, 2019)

Taxonomization of Combinatorial Optimization Problems in Fourier Space. - Anne Elorza; Leticia Hernando; José Antonio Lozano 001 (CoRR, 2019)

Evolving Gaussian Process kernels from elementary mathematical expressions. - Ibai Roman; Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (CoRR, 2019)

A review on distance based time series classification. - Amaia Abanda; Usue Mori; José Antonio Lozano 001 (Data Min. Knowl. Discov., 2019)

Multi-Objectivising Combinatorial Optimisation Problems by Means of Elementary Landscape Decompositions. - Josu Ceberio; Borja Calvo; Alexander Mendiburu; José Antonio Lozano 001 (Evol. Comput., 2019)

Anatomy of the Attraction Basins: Breaking with the Intuition. - Leticia Hernando; Alexander Mendiburu; José Antonio Lozano 001 (Evol. Comput., 2019)

Aggregated outputs by linear models: An application on marine litter beaching prediction. - Jerónimo Hernández-González; Iñaki Inza; Igor Granado; Oihane C. Basurko; Jose A. Fernandes; José Antonio Lozano 001 (Inf. Sci., 2019)

Early classification of time series using multi-objective optimization techniques. - Usue Mori; Alexander Mendiburu; Isabel Marta Miranda; José Antonio Lozano 001 (Inf. Sci., 2019)

Detection of sand dunes on Mars using a regular vine-based classification approach. - Diana Carrera; Lourenço P. C. Bandeira; Roberto Santana 001; José Antonio Lozano 001 (Knowl. Based Syst., 2019)

A Dialogue-Act Taxonomy for a Virtual Coach Designed to Improve the Life of Elderly. - César Montenegro; Asier López-Zorrilla; Javier Mikel Olaso; Roberto Santana 001; Raquel Justo; José Antonio Lozano 001; María Inés Torres (Multimodal Technol. Interact., 2019)

Preface. - José Antonio Lozano 001; Ke Tang 001; Xin Yao 001 (Nat. Comput., 2019)

On-line Elastic Similarity Measures for time series. - Izaskun Oregi; Aritz Pérez; Javier Del Ser; José Antonio Lozano 001 (Pattern Recognit., 2019)

A Note on the Behavior of Majority Voting in Multi-Class Domains with Biased Annotators. - Jerónimo Hernández-González; Iñaki Inza; José Antonio Lozano 001 (IEEE Trans. Knowl. Data Eng., 2019)

Journey to the center of the linear ordering problem. - Leticia Hernando; Alexander Mendiburu; José Antonio Lozano 001 (GECCO, 2020)

Transfer learning in hierarchical dialogue topic classification with neural networks*. - César Montenegro; Roberto Santana 001; José Antonio Lozano 001 (IJCNN, 2020)

Exploring Gaps in DeepFool in Search of More Effective Adversarial Perturbations. - Jon Vadillo; Roberto Santana 001; José Antonio Lozano 001 (LOD (2), 2020)

Analyzing rare event, anomaly, novelty and outlier detection terms under the supervised classification framework. - Ander Carreño; Iñaki Inza; José Antonio Lozano 001 (Artif. Intell. Rev., 2020)

A revisited branch-and-cut algorithm for large-scale orienteering problems. - Gorka Kobeaga; María Merino 001; José Antonio Lozano 001 (CoRR, 2020)

Probabilistic Load Forecasting Based on Adaptive Online Learning. - Verónica Álvarez; Santiago Mazuelas; José Antonio Lozano 001 (CoRR, 2020)

An efficient K-means clustering algorithm for tall data. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (Data Min. Knowl. Discov., 2020)

Robust image classification against adversarial attacks using elastic similarity measures between edge count sequences. - Izaskun Oregi; Javier Del Ser; Aritz Pérez; José Antonio Lozano 001 (Neural Networks, 2020)

Mutual information based feature subset selection in multivariate time series classification. - Josu Ircio; Aizea Lojo; Usue Mori; José Antonio Lozano 001 (Pattern Recognit., 2020)

A General Framework Based on Walsh Decomposition for Combinatorial Optimization Problems. - Imanol Unanue; María Merino 001; José Antonio Lozano 001 (CEC, 2021)

The EMPATHIC Virtual Coach: a demo. - Javier Mikel Olaso; Alain Vázquez; Leila Ben Letaifa; Mikel de Velasco; Aymen Mtibaa; Mohamed Amine Hmani; Dijana Petrovska-Delacrétaz; Gérard Chollet; César Montenegro; Asier López-Zorrilla; Raquel Justo; Roberto Santana 001; et al. (ICMI, 2021)

Evolution of Gaussian Process kernels for machine translation post-editing effort estimation. - Ibai Roman; Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (Ann. Math. Artif. Intell., 2021)

On solving cycle problems with Branch-and-Cut: extending shrinking and exact subcycle elimination separation algorithms. - Gorka Kobeaga; María Merino 001; José Antonio Lozano 001 (Ann. Oper. Res., 2021)

When and How to Fool Explainable Models (and Humans) with Adversarial Examples. - Jon Vadillo; Roberto Santana 001; José Antonio Lozano 001 (CoRR, 2021)

Analysis of the sensitivity of the End-Of-Turn Detection task to errors generated by the Automatic Speech Recognition process. - César Montenegro; Roberto Santana 001; José Antonio Lozano 001 (Eng. Appl. Artif. Intell., 2021)

Evolving Gaussian process kernels from elementary mathematical expressions for time series extrapolation. - Ibai Roman; Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (Neurocomputing, 2021)

Water leak detection using self-supervised time series classification. - Ane Blázquez-García; Angel Conde; Usue Mori; José Antonio Lozano 001 (Inf. Sci., 2021)

In-depth analysis of SVM kernel learning and its components. - Ibai Roman; Roberto Santana 001; Alexander Mendiburu; José Antonio Lozano 001 (Neural Comput. Appl., 2021)

Merge Nondominated Sorting Algorithm for Many-Objective Optimization. - Javier Moreno 004; Daniel Rodríguez 001; Antonio J. Nebro; José Antonio Lozano 001 (IEEE Trans. Cybern., 2021)

A Cheap Feature Selection Approach for the K-Means Algorithm. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (IEEE Trans. Neural Networks Learn. Syst., 2021)

Learning a Battery of COVID-19 Mortality Prediction Models by Multi-objective Optimization. - Mario Martínez-García; Susana García-Gutierrez; Rubén Armañanzas; Adrián Díaz; Iñaki Inza; José Antonio Lozano 001 (AIME, 2022)

Hyper-parameter Optimization Using Continuation Algorithms. - Jairo Rojas-Delgado; J. A. Jiménez; Rafael Bello 001; José Antonio Lozano 001 (MIC, 2022)

Transitions from P to NP-hardness: the case of the Linear Ordering Problem. - Anne Elorza; Leticia Hernando; José Antonio Lozano 001 (CEC, 2022)

Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees. - Verónica Álvarez; Santiago Mazuelas; José Antonio Lozano 001 (ICML, 2022)

Fuzzy Approach for the Temporary Logistics Hubs' Selection Planning in Disaster Region. - Gia Sirbiladze; Janusz Kacprzyk; José Antonio Lozano 001; Bezhan Ghvaberidze; Bidzina Midodashvili; Bidzina Matsaberidze (IS, 2022)

Fuzzy Model of Humanitarian Relief Logistics for the Shelters' Location in the Disaster Region and Evacuation of Population. - Gia Sirbiladze; Janusz Kacprzyk; José Antonio Lozano 001; Bezhan Ghvaberidze; Bidzina Midodashvili; Bidzina Matsaberidze (IS, 2022)

Fuzzy Approach to Planning of Service Centers Location and Goods Transportation Routes in the Disaster Region. - Gia Sirbiladze; Janusz Kacprzyk; José Antonio Lozano 001; Bezhan Ghvaberidze; Bidzina Midodashvili; Bidzina Matsaberidze (IS, 2022)

A Multivariate Time Series Streaming Classifier for Predicting Hard Drive Failures [Application Notes]. - Josu Ircio; Aizea Lojo; José Antonio Lozano 001; Usue Mori (IEEE Comput. Intell. Mag., 2022)

A Survey on Preserving Fairness Guarantees in Changing Environments. - Ainhize Barrainkua; Paula Gordaliza; José Antonio Lozano 001; Novi Quadrianto (CoRR, 2022)

A Review on Outlier/Anomaly Detection in Time Series Data. - Ane Blázquez-García; Angel Conde; Usue Mori; José Antonio Lozano 001 (ACM Comput. Surv., 2022)

Ad-hoc explanation for time series classification. - Amaia Abanda; Usue Mori; José Antonio Lozano 001 (Knowl. Based Syst., 2022)

Analysis of dominant classes in universal adversarial perturbations. - Jon Vadillo; Roberto Santana 001; José Antonio Lozano 001 (Knowl. Based Syst., 2022)

A mathematical analysis of EDAs with distance-based exponential models. - Imanol Unanue; María Merino 001; José Antonio Lozano 001 (Memetic Comput., 2022)

An active adaptation strategy for streaming time series classification based on elastic similarity measures. - Izaskun Oregi; Aritz Pérez; Javier Del Ser; José Antonio Lozano 001 (Neural Comput. Appl., 2022)

Time series classifier recommendation by a meta-learning approach. - Amaia Abanda; Usue Mori; José Antonio Lozano 001 (Pattern Recognit., 2022)

Bayesian Performance Analysis for Algorithm Ranking Comparison. - Jairo Rojas-Delgado; Josu Ceberio; Borja Calvo; José Antonio Lozano 001 (IEEE Trans. Evol. Comput., 2022)

EDA++: Estimation of Distribution Algorithms With Feasibility Conserving Mechanisms for Constrained Continuous Optimization. - Abolfazl Shirazi; Josu Ceberio; José Antonio Lozano 001 (IEEE Trans. Evol. Comput., 2022)

An Efficient Split-Merge Re-Start for the $K$K-Means Algorithm. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (IEEE Trans. Knowl. Data Eng., 2022)

An Improved Version of MMOEA/DC Based on Alternative Clustering Definitions. - Kaoutar Senhaji; Carlos A. Coello Coello; José Antonio Lozano 001 (CEC, 2023)

The Natural Bias of Artificial Instances. - Imanol Unanue; María Merino 001; José Antonio Lozano 001 (CEC, 2023)

Dependable and Resilient Emergency MAGDM Approach for the Selection of HADCs. - Gia Sirbiladze; Janusz Kacprzyk; Bidzina Midodashvili; Bezhan Ghvaberidze; José Antonio Lozano 001; Tinatin Davitashvili (DESSERT, 2023)

Evidence Theory and Fuzzy Discriminations in Dependable and Resilient Interactive MADM. Application in Emergency Psychiatric Diagnostics. - Gia Sirbiladze; Janusz Kacprzyk; Bidzina Midodashvili; Bezhan Ghvaberidze; José Antonio Lozano 001; Tinatin Davitashvili (DESSERT, 2023)

Analyzing the Fourier Representation of Permutation-Based Combinatorial Optimization Problems. - José Antonio Lozano 001 (FOGA, 2023)

Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification. - Roberto Santana 001; Ivan Hidalgo-Cenalmor; Unai Garciarena; Alexander Mendiburu; José Antonio Lozano 001 (GECCO Companion, 2023)

New Knowledge about the Elementary Landscape Decomposition for Solving the Quadratic Assignment Problem. - Xabier Benavides; Josu Ceberio; Leticia Hernando; José Antonio Lozano 001 (GECCO, 2023)

On the Use of Second Order Neighbors to Escape from Local Optima. - Manuel Torralbo; Leticia Hernando; Ernesto Contreras-Torres; José Antonio Lozano 001 (GECCO, 2023)

Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees. - Verónica Álvarez; Santiago Mazuelas; José Antonio Lozano 001 (NeurIPS, 2023)

Uncertainty in Fairness Assessment: Maintaining Stable Conclusions Despite Fluctuations. - Ainhize Barrainkua; Paula Gordaliza; José Antonio Lozano 001; Novi Quadrianto (CoRR, 2023)

Time-dependent Probabilistic Generative Models for Disease Progression. - Onintze Zaballa; Aritz Pérez; Elisa Gómez-Inhiesto; Teresa Acaiturri Ayesta; José Antonio Lozano 001 (CoRR, 2023)

Trajectory optimization of space vehicle in rendezvous proximity operation with evolutionary feasibility conserving techniques. - Abolfazl Shirazi; Josu Ceberio; José Antonio Lozano 001 (Eng. Appl. Artif. Intell., 2023)

Introducing multi-dimensional hierarchical classification: Characterization, solving strategies and performance measures. - César Montenegro; Roberto Santana 001; José Antonio Lozano 001 (Neurocomputing, 2023)

Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions. - Jon Vadillo; Roberto Santana 001; José Antonio Lozano 001 (J. Mach. Learn. Res., 2023)

Fast computation of cluster validity measures for bregman divergences and benefits. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (Pattern Recognit. Lett., 2023)

LASSO for streaming data with adaptative filtering. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (Stat. Comput., 2023)

Learning the progression patterns of treatments using a probabilistic generative model. - Onintze Zaballa; Aritz Pérez; Elisa Gómez-Inhiesto; Teresa Acaiturri Ayesta; José Antonio Lozano 001 (J. Biomed. Informatics, 2023)

SNDProb: A Probabilistic Approach for Streaming Novelty Detection. - Ander Carreño; Iñaki Inza; José Antonio Lozano 001 (IEEE Trans. Knowl. Data Eng., 2023)

Delineation of site-specific management zones using estimation of distribution algorithms. - Jonás Velasco; Salvador Vicencio; José Antonio Lozano 001; Néstor M. Cid-García (Int. Trans. Oper. Res., 2023)

Selective Imputation for Multivariate Time Series Datasets With Missing Values. - Ane Blázquez-García; Kristoffer Wickstrøm; Shujian Yu; Karl Øyvind Mikalsen; Ahcène Boubekki; Angel Conde; Usue Mori; Robert Jenssen; José Antonio Lozano 001 (IEEE Trans. Knowl. Data Eng., 2023)

Minimum Recall-Based Loss Function for Imbalanced Time Series Classification. - Josu Ircio; Aizea Lojo; Usue Mori; Simon Malinowski; José Antonio Lozano 001 (IEEE Trans. Knowl. Data Eng., 2023)

Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results. - Ainhize Barrainkua; Paula Gordaliza; José Antonio Lozano 001; Novi Quadrianto (AISTATS, 2024)

Self-Composing Policies for Scalable Continual Reinforcement Learning. - Mikel Malagon; Josu Ceberio; José Antonio Lozano 001 (ICML, 2024)

Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks. - Jon Vadillo; Roberto Santana 001; José Antonio Lozano 001; Marta Kwiatkowska (CoRR, 2024)

Dancing in the Shadows: Harnessing Ambiguity for Fairer Classifiers. - Ainhize Barrainkua; Paula Gordaliza; José Antonio Lozano 001; Novi Quadrianto (CoRR, 2024)

Craftium: An Extensible Framework for Creating Reinforcement Learning Environments. - Mikel Malagon; Josu Ceberio; José Antonio Lozano 001 (CoRR, 2024)

Characterization of rankings generated by pseudo-Boolean functions. - Imanol Unanue; María Merino 001; José Antonio Lozano 001 (Swarm Evol. Comput., 2024)

A probabilistic generative model to discover the treatments of coexisting diseases with missing data. - Onintze Zaballa; Aritz Pérez; Elisa Gómez-Inhiesto; Teresa Acaiturri Ayesta; José Antonio Lozano 001 (Comput. Methods Programs Biomed., 2024)

A revisited branch-and-cut algorithm for large-scale orienteering problems. - Gorka Kobeaga; Jairo Rojas-Delgado; María Merino 001; José Antonio Lozano 001 (Eur. J. Oper. Res., 2024)

A roadmap for solving optimization problems with estimation of distribution algorithms. - Josu Ceberio; Alexander Mendiburu; José Antonio Lozano 001 (Nat. Comput., 2024)

Fast $K$-Medoids With the $l_{1}$-Norm. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (IEEE Trans. Artif. Intell., 2024)

Learning the Graph Structure of Regular Vine-Copulas from Dependence Lists. - Diana Carrera; Roberto Santana 001; José Antonio Lozano 001 (ACM Trans. Evol. Learn. Optim., 2024)

Extending the learning using privileged information paradigm to logistic regression. - Mario Martínez-García; Susana García-Gutierrez; Lasai Barreñada; Iñaki Inza; José Antonio Lozano 001 (Neurocomputing, 2025)

Teacher privileged distillation: How to deal with imperfect teachers? - Mario Martínez-García; Iñaki Inza; José Antonio Lozano 001 (Knowl. Based Syst., 2025)

Supervised Learning with Evolving Tasks and Performance Guarantees. - Verónica Álvarez; Santiago Mazuelas; José Antonio Lozano 001 (CoRR, 2025)

A Review on Self-Supervised Learning for Time Series Anomaly Detection: Recent Advances and Open Challenges. - Aitor Sánchez-Ferrera; Borja Calvo; José Antonio Lozano 001 (CoRR, 2025)

Adversarial Attacks in Explainable Machine Learning: A Survey of Threats Against Models and Humans. - Jon Vadillo; Roberto Santana 001; José Antonio Lozano 001 (WIREs Data. Mining. Knowl. Discov., 2025)

The Decoupled Risk Landscape in Performative Prediction. - Javier Sanguino; Thomas Kehrenberg; José Antonio Lozano 001; Novi Quadrianto (CoRR, 2025)

Preserving the Fairness Guarantees of Classifiers in Changing Environments: A Survey. - Ainhize Barrainkua; Paula Gordaliza; José Antonio Lozano 001; Novi Quadrianto (ACM Comput. Surv., 2025)

NeuCoReClass AD: Redefining Self-Supervised Time Series Anomaly Detection. - Aitor Sánchez-Ferrera; Usue Mori; Borja Calvo; José Antonio Lozano 001 (CoRR, 2025)

Transforming Combinatorial Optimization Problems in Fourier Space: Consequences and Uses. - Anne Elorza; Xabier Benavides; Josu Ceberio; Leticia Hernando; José Antonio Lozano 001 (IEEE Trans. Evol. Comput., 2025)