José Antonio Lozano

Orcid: 0000-0002-4683-8111

Affiliations:
  • University of the Basque Country, Department of Computer Science and Artificial Intelligence


According to our database1, José Antonio Lozano authored at least 284 papers between 1994 and 2024.

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Bibliography

2024
Fast $K$-Medoids With the $l_{1}$-Norm.
IEEE Trans. Artif. Intell., April, 2024

A roadmap for solving optimization problems with estimation of distribution algorithms.
Nat. Comput., March, 2024

A revisited branch-and-cut algorithm for large-scale orienteering problems.
Eur. J. Oper. Res., February, 2024

A probabilistic generative model to discover the treatments of coexisting diseases with missing data.
Comput. Methods Programs Biomed., January, 2024

Characterization of rankings generated by pseudo-Boolean functions.
Swarm Evol. Comput., 2024

Craftium: An Extensible Framework for Creating Reinforcement Learning Environments.
CoRR, 2024

Dancing in the Shadows: Harnessing Ambiguity for Fairer Classifiers.
CoRR, 2024

Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks.
CoRR, 2024

Self-Composing Policies for Scalable Continual Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Minimum Recall-Based Loss Function for Imbalanced Time Series Classification.
IEEE Trans. Knowl. Data Eng., October, 2023

Selective Imputation for Multivariate Time Series Datasets With Missing Values.
IEEE Trans. Knowl. Data Eng., September, 2023

Delineation of site-specific management zones using estimation of distribution algorithms.
Int. Trans. Oper. Res., July, 2023

SNDProb: A Probabilistic Approach for Streaming Novelty Detection.
IEEE Trans. Knowl. Data Eng., June, 2023

Learning the progression patterns of treatments using a probabilistic generative model.
J. Biomed. Informatics, January, 2023

LASSO for streaming data with adaptative filtering.
Stat. Comput., 2023

Fast computation of cluster validity measures for bregman divergences and benefits.
Pattern Recognit. Lett., 2023

Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions.
J. Mach. Learn. Res., 2023

Introducing multi-dimensional hierarchical classification: Characterization, solving strategies and performance measures.
Neurocomputing, 2023

Trajectory optimization of space vehicle in rendezvous proximity operation with evolutionary feasibility conserving techniques.
Eng. Appl. Artif. Intell., 2023

Time-dependent Probabilistic Generative Models for Disease Progression.
CoRR, 2023

Uncertainty in Fairness Assessment: Maintaining Stable Conclusions Despite Fluctuations.
CoRR, 2023

Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Use of Second Order Neighbors to Escape from Local Optima.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023

New Knowledge about the Elementary Landscape Decomposition for Solving the Quadratic Assignment Problem.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Analyzing the Fourier Representation of Permutation-Based Combinatorial Optimization Problems.
Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023

Evidence Theory and Fuzzy Discriminations in Dependable and Resilient Interactive MADM. Application in Emergency Psychiatric Diagnostics.
Proceedings of the 13th International Conference on Dependable Systems, 2023

Dependable and Resilient Emergency MAGDM Approach for the Selection of HADCs.
Proceedings of the 13th International Conference on Dependable Systems, 2023

The Natural Bias of Artificial Instances.
Proceedings of the IEEE Congress on Evolutionary Computation, 2023

An Improved Version of MMOEA/DC Based on Alternative Clustering Definitions.
Proceedings of the IEEE Congress on Evolutionary Computation, 2023

2022
An Efficient Split-Merge Re-Start for the $K$K-Means Algorithm.
IEEE Trans. Knowl. Data Eng., 2022

EDA++: Estimation of Distribution Algorithms With Feasibility Conserving Mechanisms for Constrained Continuous Optimization.
IEEE Trans. Evol. Comput., 2022

Bayesian Performance Analysis for Algorithm Ranking Comparison.
IEEE Trans. Evol. Comput., 2022

Time series classifier recommendation by a meta-learning approach.
Pattern Recognit., 2022

An active adaptation strategy for streaming time series classification based on elastic similarity measures.
Neural Comput. Appl., 2022

A mathematical analysis of EDAs with distance-based exponential models.
Memetic Comput., 2022

Analysis of dominant classes in universal adversarial perturbations.
Knowl. Based Syst., 2022

Ad-hoc explanation for time series classification.
Knowl. Based Syst., 2022

A Review on Outlier/Anomaly Detection in Time Series Data.
ACM Comput. Surv., 2022

A Survey on Preserving Fairness Guarantees in Changing Environments.
CoRR, 2022

A Multivariate Time Series Streaming Classifier for Predicting Hard Drive Failures [Application Notes].
IEEE Comput. Intell. Mag., 2022

Fuzzy Approach to Planning of Service Centers Location and Goods Transportation Routes in the Disaster Region.
Proceedings of the IEEE 11th International Conference on Intelligent Systems, 2022

Fuzzy Model of Humanitarian Relief Logistics for the Shelters' Location in the Disaster Region and Evacuation of Population.
Proceedings of the IEEE 11th International Conference on Intelligent Systems, 2022

Fuzzy Approach for the Temporary Logistics Hubs' Selection Planning in Disaster Region.
Proceedings of the IEEE 11th International Conference on Intelligent Systems, 2022

Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees.
Proceedings of the International Conference on Machine Learning, 2022

Transitions from P to NP-hardness: the case of the Linear Ordering Problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022

Hyper-parameter Optimization Using Continuation Algorithms.
Proceedings of the Metaheuristics - 14th International Conference, 2022

Learning a Battery of COVID-19 Mortality Prediction Models by Multi-objective Optimization.
Proceedings of the Artificial Intelligence in Medicine, 2022

2021
A Cheap Feature Selection Approach for the K-Means Algorithm.
IEEE Trans. Neural Networks Learn. Syst., 2021

Merge Nondominated Sorting Algorithm for Many-Objective Optimization.
IEEE Trans. Cybern., 2021

In-depth analysis of SVM kernel learning and its components.
Neural Comput. Appl., 2021

Water leak detection using self-supervised time series classification.
Inf. Sci., 2021

Evolving Gaussian process kernels from elementary mathematical expressions for time series extrapolation.
Neurocomputing, 2021

Analysis of the sensitivity of the End-Of-Turn Detection task to errors generated by the Automatic Speech Recognition process.
Eng. Appl. Artif. Intell., 2021

When and How to Fool Explainable Models (and Humans) with Adversarial Examples.
CoRR, 2021

On solving cycle problems with Branch-and-Cut: extending shrinking and exact subcycle elimination separation algorithms.
Ann. Oper. Res., 2021

Evolution of Gaussian Process kernels for machine translation post-editing effort estimation.
Ann. Math. Artif. Intell., 2021


A General Framework Based on Walsh Decomposition for Combinatorial Optimization Problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2021

2020
Mutual information based feature subset selection in multivariate time series classification.
Pattern Recognit., 2020

Robust image classification against adversarial attacks using elastic similarity measures between edge count sequences.
Neural Networks, 2020

An efficient K-means clustering algorithm for tall data.
Data Min. Knowl. Discov., 2020

Probabilistic Load Forecasting Based on Adaptive Online Learning.
CoRR, 2020

A revisited branch-and-cut algorithm for large-scale orienteering problems.
CoRR, 2020

Analyzing rare event, anomaly, novelty and outlier detection terms under the supervised classification framework.
Artif. Intell. Rev., 2020

Exploring Gaps in DeepFool in Search of More Effective Adversarial Perturbations.
Proceedings of the Machine Learning, Optimization, and Data Science, 2020

Transfer learning in hierarchical dialogue topic classification with neural networks<sup>*</sup>.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Journey to the center of the linear ordering problem.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019
A Note on the Behavior of Majority Voting in Multi-Class Domains with Biased Annotators.
IEEE Trans. Knowl. Data Eng., 2019

On-line Elastic Similarity Measures for time series.
Pattern Recognit., 2019

Preface.
Nat. Comput., 2019

A Dialogue-Act Taxonomy for a Virtual Coach Designed to Improve the Life of Elderly.
Multimodal Technol. Interact., 2019

Detection of sand dunes on Mars using a regular vine-based classification approach.
Knowl. Based Syst., 2019

Early classification of time series using multi-objective optimization techniques.
Inf. Sci., 2019

Aggregated outputs by linear models: An application on marine litter beaching prediction.
Inf. Sci., 2019

Anatomy of the Attraction Basins: Breaking with the Intuition.
Evol. Comput., 2019

Multi-Objectivising Combinatorial Optimisation Problems by Means of Elementary Landscape Decompositions.
Evol. Comput., 2019

A review on distance based time series classification.
Data Min. Knowl. Discov., 2019

Evolving Gaussian Process kernels from elementary mathematical expressions.
CoRR, 2019

Taxonomization of Combinatorial Optimization Problems in Fourier Space.
CoRR, 2019

An Experimental Study in Adaptive Kernel Selection for Bayesian Optimization.
IEEE Access, 2019


Data generation approaches for topic classification in multilingual spoken dialog systems.
Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, 2019

Evolving Gaussian Process Kernels for Translation Editing Effort Estimation.
Proceedings of the Learning and Intelligent Optimization - 13th International Conference, 2019

Bayesian Optimization Approaches for Massively Multi-modal Problems.
Proceedings of the Learning and Intelligent Optimization - 13th International Conference, 2019

Sentiment analysis with genetically evolved gaussian kernels.
Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Characterising the rankings produced by combinatorial optimisation problems and finding their intersections.
Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Bayesian performance analysis for black-box optimization benchmarking.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019

Hybrid Heuristics for the Linear Ordering Problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2019

2018
Multi-start Methods.
Proceedings of the Handbook of Heuristics., 2018

Early Classification of Time Series by Simultaneously Optimizing the Accuracy and Earliness.
IEEE Trans. Neural Networks Learn. Syst., 2018

Estimating attraction basin sizes of combinatorial optimization problems.
Prog. Artif. Intell., 2018

Effects of Reducing VMs Management Times on Elastic Applications.
J. Grid Comput., 2018

The weighted independent domination problem: Integer linear programming models and metaheuristic approaches.
Eur. J. Oper. Res., 2018

A system for airport weather forecasting based on circular regression trees.
Environ. Model. Softw., 2018

Merge Non-Dominated Sorting Algorithm for Many-Objective Optimization.
CoRR, 2018

An efficient K -means clustering algorithm for massive data.
CoRR, 2018

An efficient evolutionary algorithm for the orienteering problem.
Comput. Oper. Res., 2018

Learning to classify software defects from crowds: A novel approach.
Appl. Soft Comput., 2018

Approximating the maximum weighted decomposable graph problem with applications to probabilistic graphical models.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

The Relationship Between Graphical Representations of Regular Vine Copulas and Polytrees.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications, 2018

Adversarial Sample Crafting for Time Series Classification with Elastic Similarity Measures.
Proceedings of the Intelligent Distributed Computing XII, 2018

Distance-based exponential probability models on constrained combinatorial optimization problems.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

Bayesian inference for algorithm ranking analysis.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

Are the Artificially Generated Instances Uniform in Terms of Difficulty?
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

Hill-Climbing Algorithm: Let's Go for a Walk Before Finding the Optimum.
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

Distance-Based Exponential Probability Models for Constrained Combinatorial Problems.
Proceedings of the Advances in Artificial Intelligence, 2018

2017
Editorial: A Successful Year and Looking Forward to 2017 and Beyond.
IEEE Trans. Neural Networks Learn. Syst., 2017

An investigation of clustering strategies in many-objective optimization: the I-Multi algorithm as a case study.
Swarm Intell., 2017

Measuring the class-imbalance extent of multi-class problems.
Pattern Recognit. Lett., 2017

Transfer weight functions for injecting problem information in the multi-objective CMA-ES.
Memetic Comput., 2017

An efficient approximation to the K-means clustering for massive data.
Knowl. Based Syst., 2017

Learning from Proportions of Positive and Unlabeled Examples.
Int. J. Intell. Syst., 2017

Reliable early classification of time series based on discriminating the classes over time.
Data Min. Knowl. Discov., 2017

Conference Report on 2017 IEEE Congress on Evolutionary Computation (IEEE CEC 2017) [Conference Reports].
IEEE Comput. Intell. Mag., 2017

On-Line Dynamic Time Warping for Streaming Time Series.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Different scenarios for survival analysis of evolutionary algorithms.
Proceedings of the Genetic and Evolutionary Computation Conference, 2017

The Weighted Independent Domination Problem: ILP Model and Algorithmic Approaches.
Proceedings of the Evolutionary Computation in Combinatorial Optimization, 2017

Evolutionary algorithms to optimize low-thrust trajectory design in spacecraft orbital precession mission.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

Nature-inspired approaches for distance metric learning in multivariate time series classification.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

General chair's welcome.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

Are we generating instances uniformly at random?
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

A square lattice probability model for optimising the Graph Partitioning Problem.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

Combining CMA-ES and MOEA/DD for many-objective optimization.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

2016
Semisupervised Multiclass Classification Problems With Scarcity of Labeled Data: A Theoretical Study.
IEEE Trans. Neural Networks Learn. Syst., 2016

Similarity Measure Selection for Clustering Time Series Databases.
IEEE Trans. Knowl. Data Eng., 2016

Estimation of the Distribution Algorithm With a Stochastic Local Search for Uncertain Capacitated Arc Routing Problems.
IEEE Trans. Evol. Comput., 2016

A Sparse Spectral Clustering Framework via Multiobjective Evolutionary Algorithm.
IEEE Trans. Evol. Comput., 2016

A Tunable Generator of Instances of Permutation-Based Combinatorial Optimization Problems.
IEEE Trans. Evol. Comput., 2016

Distance Measures for Time Series in R: The TSdist Package.
R J., 2016

Weak supervision and other non-standard classification problems: A taxonomy.
Pattern Recognit. Lett., 2016

Vine copula classifiers for the mind reading problem.
Prog. Artif. Intell., 2016

A review of message passing algorithms in estimation of distribution algorithms.
Nat. Comput., 2016

Efficient approximation of probability distributions with k-order decomposable models.
Int. J. Approx. Reason., 2016

An efficient K-means algorithm for Massive Data.
CoRR, 2016

Construct, Merge, Solve & Adapt A new general algorithm for combinatorial optimization.
Comput. Oper. Res., 2016

Analyzing the Performance of Allocation Strategies Based on Space-Filling Curves.
Proceedings of the Job Scheduling Strategies for Parallel Processing, 2016

Bayesian optimization for parameter tuning in evolutionary algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

Estimating Attraction Basin Sizes.
Proceedings of the Advances in Artificial Intelligence, 2016

A Note on the Boltzmann Distribution and the Linear Ordering Problem.
Proceedings of the Advances in Artificial Intelligence, 2016

2015
Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints.
IEEE Trans. Robotics, 2015

Locality-aware policies to improve job scheduling on 3D tori.
J. Supercomput., 2015

A Boltzmann-Based Estimation of Distribution Algorithm for a General Resource Scheduling Model.
IEEE Trans. Evol. Comput., 2015

Comprehensive characterization of the behaviors of estimation of distribution algorithms.
Theor. Comput. Sci., 2015

Gene-Gene Interactions Detection Using a Two-stage Model.
J. Comput. Biol., 2015

Multidimensional Learning from Crowds: Usefulness and Application of Expertise Detection.
Int. J. Intell. Syst., 2015

Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies.
J. Grid Comput., 2015

The linear ordering problem revisited.
Eur. J. Oper. Res., 2015

Mathematical programming strategies for solving the minimum common string partition problem.
Eur. J. Oper. Res., 2015

Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species.
Ecol. Informatics, 2015

Computing factorized approximations of Pareto-fronts using mNM-landscapes and Boltzmann distributions.
CoRR, 2015

A review of distances for the Mallows and Generalized Mallows estimation of distribution algorithms.
Comput. Optim. Appl., 2015

Multi-view classification of psychiatric conditions based on saccades.
Appl. Soft Comput., 2015

An Artificial Bioindicator System for Network Intrusion Detection.
Artif. Life, 2015

Dealing with the evaluation of supervised classification algorithms.
Artif. Intell. Rev., 2015

Multi-objective NM-Landscapes.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Kernels of Mallows Models for Solving Permutation-based Problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Evolving MNK-landscapes with structural constraints.
Proceedings of the IEEE Congress on Evolutionary Computation, 2015

Mixtures of Generalized Mallows models for solving the quadratic assignment problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2015

A Novel Weakly Supervised Problem: Learning from Positive-Unlabeled Proportions.
Proceedings of the Advances in Artificial Intelligence, 2015

Multi-objectivising the Quadratic Assignment Problem by Means of an Elementary Landscape Decomposition.
Proceedings of the Advances in Artificial Intelligence, 2015

2014
A Distance-Based Ranking Model Estimation of Distribution Algorithm for the Flowshop Scheduling Problem.
IEEE Trans. Evol. Comput., 2014

Application-aware metrics for partition selection in cube-shaped topologies.
Parallel Comput., 2014

Assisting in search heuristics selection through multidimensional supervised classification: A case study on software testing.
Inf. Sci., 2014

A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments.
J. Grid Comput., 2014

A fast implementation of the first fit contiguous partitioning strategy for cubic topologies.
Concurr. Comput. Pract. Exp., 2014

Customized Selection in Estimation of Distribution Algorithms.
Proceedings of the Simulated Evolution and Learning - 10th International Conference, 2014

Learning Maximum Weighted (k+1)-Order Decomposable Graphs by Integer Linear Programming.
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Iterative Probabilistic Tree Search for the Minimum Common String Partition Problem.
Proceedings of the Hybrid Metaheuristics - 9th International Workshop, HM 2014, 2014

Optimization of Application Placement Towards a Greener Cloud Infrastructure.
Proceedings of the Applications of Evolutionary Computation - 17th European Conference, 2014

Estimation of Distribution Algorithms based Unmanned Aerial Vehicle path planner using a new coordinate system.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014

Extending distance-based ranking models in estimation of distribution algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014

2013
A general framework for the statistical analysis of the sources of variance for classification error estimators.
Pattern Recognit., 2013

Learning Bayesian network classifiers from label proportions.
Pattern Recognit., 2013

Significance tests or confidence intervals: which are preferable for the comparison of classifiers?
J. Exp. Theor. Artif. Intell., 2013

Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting.
Environ. Model. Softw., 2013

An Evaluation of Methods for Estimating the Number of Local Optima in Combinatorial Optimization Problems.
Evol. Comput., 2013

On the Taxonomy of Optimization Problems Under Estimation of Distribution Algorithms.
Evol. Comput., 2013

Combinatorial Optimization by Learning and Simulation of Bayesian Networks
CoRR, 2013

Message Passing Methods for Estimation of Distribution Algorithms Based on Markov Networks.
Proceedings of the Swarm, Evolutionary, and Memetic Computing, 2013

Critical Issues in Model-Based Surrogate Functions in Estimation of Distribution Algorithms.
Proceedings of the Swarm, Evolutionary, and Memetic Computing, 2013

Generating Customized Landscapes in Permutation-Based Combinatorial Optimization Problems.
Proceedings of the Learning and Intelligent Optimization - 7th International Conference, 2013

Understanding Instance Complexity in the Linear Ordering Problem.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2013, 2013

Symmetry in evolutionary and estimation of distribution algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

The Plackett-Luce ranking model on permutation-based optimization problems.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

Multidimensional k-Interaction Classifier: Taking Advantage of All the Information Contained in Low Order Interactions.
Proceedings of the Advances in Artificial Intelligence, 2013

Learning from Crowds in Multi-dimensional Classification Domains.
Proceedings of the Advances in Artificial Intelligence, 2013

2012
Using Multidimensional Bayesian Network Classifiers to Assist the Treatment of Multiple Sclerosis.
IEEE Trans. Syst. Man Cybern. Part C, 2012

Toward Understanding EDAs Based on Bayesian Networks Through a Quantitative Analysis.
IEEE Trans. Evol. Comput., 2012

A review on estimation of distribution algorithms in permutation-based combinatorial optimization problems.
Prog. Artif. Intell., 2012

Wrapper positive Bayesian network classifiers.
Knowl. Inf. Syst., 2012

Approaching Sentiment Analysis by using semi-supervised learning of multi-dimensional classifiers.
Neurocomputing, 2012

A Markovianity based optimisation algorithm.
Genet. Program. Evolvable Mach., 2012

An interactive optimization approach to a real-world oceanographic campaign planning problem.
Appl. Intell., 2012

Evolving NK-complexity for evolutionary solvers.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

An analysis of the use of probabilistic modeling for synaptic connectivity prediction from genomic data.
Proceedings of the IEEE Congress on Evolutionary Computation, 2012

Structural transfer using EDAs: An application to multi-marker tagging SNP selection.
Proceedings of the IEEE Congress on Evolutionary Computation, 2012

2011
A Preprocessing Procedure for Haplotype Inference by Pure Parsimony.
IEEE ACM Trans. Comput. Biol. Bioinform., 2011

Optimization-based mapping framework for parallel applications.
J. Parallel Distributed Comput., 2011

Introducing the Mallows Model on Estimation of Distribution Algorithms.
Proceedings of the Neural Information Processing - 18th International Conference, 2011

A preliminary study on EDAs for permutation problems based on marginal-based models.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

A study on the complexity of TSP instances under the 2-exchange neighbor system.
Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, 2011

On the limits of effectiveness in estimation of distribution algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2011

Learning Probability Distributions over Permutations by Means of Fourier Coefficients.
Proceedings of the Advances in Artificial Intelligence, 2011

2010
A Review on Parallel Estimation of Distribution Algorithms.
Proceedings of the Parallel and Distributed Computational Intelligence, 2010

Sensitivity Analysis of k-Fold Cross Validation in Prediction Error Estimation.
IEEE Trans. Pattern Anal. Mach. Intell., 2010

Learning Factorizations in Estimation of Distribution Algorithms Using Affinity Propagation.
Evol. Comput., 2010

Multi-marker tagging single nucleotide polymorphism selection using estimation of distribution algorithms.
Artif. Intell. Medicine, 2010

Strategies to Map Parallel Applications onto Meshes.
Proceedings of the Distributed Computing and Artificial Intelligence, 2010

Estimation of Bayesian networks algorithms in a class of complex networks.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010

2009
Guest Editorial: Special Issue on Evolutionary Algorithms Based on Probabilistic Models.
IEEE Trans. Evol. Comput., 2009

Feature subset selection from positive and unlabelled examples.
Pattern Recognit. Lett., 2009

Research topics in discrete estimation of distribution algorithms based on factorizations.
Memetic Comput., 2009

Mining probabilistic models learned by EDAs in the optimization of multi-objective problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

A new preprocessing procedure for the haplotype inference problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2009

Analyzing the probability of the optimum in EDAs based on Bayesian networks.
Proceedings of the IEEE Congress on Evolutionary Computation, 2009

2008
Adaptive Estimation of Distribution Algorithms.
Proceedings of the Adaptive and Multilevel Metaheuristics, 2008

The Impact of Exact Probabilistic Learning Algorithms in EDAs Based on Bayesian Networks.
Proceedings of the Linkage in Evolutionary Computation, 2008

Protein Folding in Simplified Models With Estimation of Distribution Algorithms.
IEEE Trans. Evol. Comput., 2008

Inference of Population Structure Using Genetic Markers and a Bayesian Model Averaging Approach for Clustering.
J. Comput. Biol., 2008

Combining variable neighborhood search and estimation of distribution algorithms in the protein side chain placement problem.
J. Heuristics, 2008

Dynamic Search Space Transformations for Software Test Data Generation.
Comput. Intell., 2008

A review of estimation of distribution algorithms in bioinformatics.
BioData Min., 2008

Adding Probabilistic Dependencies to the Search of Protein Side Chain Configurations Using EDAs.
Proceedings of the Parallel Problem Solving from Nature, 2008

Multi-Objective Learning of Multi-Dimensional Bayesian Classifiers.
Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008

Component weighting functions for adaptive search with EDAs.
Proceedings of the IEEE Congress on Evolutionary Computation, 2008

A multi-objective approach to the Channel Assignment Problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2008

2007
Learning Bayesian classifiers from positive and unlabeled examples.
Pattern Recognit. Lett., 2007

A partially supervised classification approach to dominant and recessive human disease gene prediction.
Comput. Methods Programs Biomed., 2007

Side chain placement using estimation of distribution algorithms.
Artif. Intell. Medicine, 2007

A parallel framework for loopy belief propagation.
Proceedings of the Genetic and Evolutionary Computation Conference, 2007

The Role of a Priori Information in the Minimization of Contact Potentials by Means of Estimation of Distribution Algorithms.
Proceedings of the Evolutionary Computation, 2007

Discriminative vs. Generative Learning of Bayesian Network Classifiers.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2007

Exact Bayesian network learning in estimation of distribution algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2007

2006
Bayesian Model Averaging of Naive Bayes for Clustering.
IEEE Trans. Syst. Man Cybern. Part B, 2006

Implementation and Performance Evaluation of a Parallelization of Estimation of Bayesian Network Algorithms.
Parallel Process. Lett., 2006

Parallel EDAs to create multivariate calibration models for quantitative chemical applications.
J. Parallel Distributed Comput., 2006

Scatter Search in software testing, comparison and collaboration with Estimation of Distribution Algorithms.
Eur. J. Oper. Res., 2006

Machine learning in bioinformatics.
Briefings Bioinform., 2006

Discriminative Learning of Bayesian Network Classifiers.
Inteligencia Artif., 2006

Bayesian Model Averaging of TAN Models for Clustering.
Proceedings of the Third European Workshop on Probabilistic Graphical Models, 2006

Mixtures of Kikuchi Approximations.
Proceedings of the Machine Learning: ECML 2006, 2006

Evaluation of Parallel EDAs to Create Chemical Calibration Models.
Proceedings of the Second International Conference on e-Science and Grid Technologies (e-Science 2006), 2006

2005
Parallel Implementation of EDAs Based on Probabilistic Graphical Models.
IEEE Trans. Evol. Comput., 2005

Editorial.
Mach. Learn., 2005

Globally Multimodal Problem Optimization Via an Estimation of Distribution Algorithm Based on Unsupervised Learning of Bayesian Networks.
Evol. Comput., 2005

Editorial Introduction Special Issue on Estimation of Distribution Algorithms.
Evol. Comput., 2005

On The Performance Of Estimation Of Distribution Algorithms Applied To Software Testing.
Appl. Artif. Intell., 2005

Average Time Complexity of Estimation of Distribution Algorithms.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005

Parallel and Multi-Objective EDAs to Create Multivariate Calibration Models for Quantitative Chemical Applications.
Proceedings of the 34th International Conference on Parallel Processing Workshops (ICPP 2005 Workshops), 2005

Discriminative Learning of Bayesian Network Classifiers via the TM Algorithm.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2005

Interactions and dependencies in estimation of distribution algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2005

A multiobjective approach to the portfolio optimization problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2005

2004
Unsupervised Learning Of Bayesian Networks Via Estimation Of Distribution Algorithms: An Application To Gene Expression Data Clustering.
Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2004

Protein Folding in 2-Dimensional Lattices with Estimation of Distribution Algorithms.
Proceedings of the Biological and Medical Data Analysis, 5th International Symposium, 2004

2003
Algoritmos de Estimación de Distribuciones en Problemas de Optimización Combinatoria.
Inteligencia Artif., 2003

Analysis of the Univariate Marginal Distribution Algorithm Modeled by Markov Chains.
Proceedings of the Artificial Neural Nets Problem Solving Methods, 2003

2002
Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction.
Mach. Learn., 2002

Synergies between evolutionary computation and probabilistic graphical models.
Int. J. Approx. Reason., 2002

Mathematical modelling of UMDA<sub>c</sub> algorithm with tournament selection. Behaviour on linear and quadratic functions.
Int. J. Approx. Reason., 2002

Unsupervised Learning of Bayesian Networks Via Estimation of Distribution Algorithms.
Proceedings of the First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002, 2002

Benefits of Data Clustering in Multimodal Function Optimization via EDAs.
Proceedings of the Estimation of Distribution Algorithms, 2002

Parallel Estimation of Distribution Algorithms.
Proceedings of the Estimation of Distribution Algorithms, 2002

Estimation of Distribution Algorithms Applied to the Job Shop Scheduling Problem: Some Preliminary Research.
Proceedings of the Estimation of Distribution Algorithms, 2002

An Introduction to Evolutionary Algorithms.
Proceedings of the Estimation of Distribution Algorithms, 2002

Mathematical Modeling of Discrete Estimation of Distribution Algorithms.
Proceedings of the Estimation of Distribution Algorithms, 2002

An Empirical Comparison of Discrete Estimation of Distribution Algorithms.
Proceedings of the Estimation of Distribution Algorithms, 2002

Experimental Results in Function Optimization with EDAs in Continuous Domain.
Proceedings of the Estimation of Distribution Algorithms, 2002

2001
Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2001

Performance evaluation of compromise conditional Gaussian networks for data clustering.
Int. J. Approx. Reason., 2001

Geographical clustering of cancer incidence by means of Bayesian networks and conditional Gaussian networks.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering.
Pattern Recognit. Lett., 2000

Analyzing the Population Based Incremental Learning Algorithm by Means of Discrete Dynamical Systems.
Complex Syst., 2000

Combinatonal Optimization by Learning and Simulation of Bayesian Networks.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

1999
Genetic Algorithms: Bridging the Convergence Gap.
Theor. Comput. Sci., 1999

Learning Bayesian networks for clustering by means of constructive induction.
Pattern Recognit. Lett., 1999

An empirical comparison of four initialization methods for the K-Means algorithm.
Pattern Recognit. Lett., 1999

Applying genetic algorithms to search for the best hierarchical clustering of a dataset.
Pattern Recognit. Lett., 1999

Representing the behaviour of supervised classification learning algorithms by Bayesian networks.
Pattern Recognit. Lett., 1999

1998
Aplicación de los algoritmos genéticos al problema del clustering jerárquico.
Inteligencia Artif., 1998

1997
Experimental Results of a Michigan-like Evolution Strategy for Non-stationary Clustering.
Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms, 1997

1996
Convergence Properties of High-order Boltzmann Machines.
Neural Networks, 1996

1994
High-order Boltzmann machines applied to the Monk's problems.
Proceedings of the 2nd European Symposium on Artificial Neural Networks, 1994


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