Alexander Mendiburu

Orcid: 0000-0002-7271-1931

According to our database1, Alexander Mendiburu authored at least 122 papers between 2002 and 2024.

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Bibliography

2024
Applicability of Neural Combinatorial Optimization: A Critical View.
ACM Trans. Evol. Learn. Optim., September, 2024

Redefining Neural Architecture Search of Heterogeneous Multinetwork Models by Characterizing Variation Operators and Model Components.
IEEE Trans. Neural Networks Learn. Syst., August, 2024

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

Factorized models in neural architecture search: Impact on computational costs and performance.
Proceedings of the International Joint Conference on Neural Networks, 2024

MARCO: A Memory-Augmented Reinforcement Framework for Combinatorial Optimization.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Neural Combinatorial Optimization by Means of Partial Solution Strategies.
Proceedings of the IEEE Congress on Evolutionary Computation, 2024

Exploring the Capabilities and Limitations of Neural Methods in the Maximum Cut.
Proceedings of the Advances in Artificial Intelligence, 2024

2023
Efficient concept drift handling for batch android malware detection models.
Pervasive Mob. Comput., December, 2023

Light up that Droid! On the Effectiveness of Static Analysis Features against App Obfuscation for Android Malware Detection.
CoRR, 2023

Towards a fair comparison and realistic evaluation framework of android malware detectors based on static analysis and machine learning.
Comput. Secur., 2023

Analyzing the interplay between transferable GANs and gradient optimizers.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 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

2022
A grammar-based GP approach applied to the design of deep neural networks.
Genet. Program. Evolvable Mach., 2022

Neural Improvement Heuristics for Preference Ranking.
CoRR, 2022

Towards a Fair Comparison and Realistic Design and Evaluation Framework of Android Malware Detectors.
CoRR, 2022

Neural Combinatorial Optimization: a New Player in the Field.
CoRR, 2022

2021
Towards Automatic Construction of Multi-Network Models for Heterogeneous Multi-Task Learning.
ACM Trans. Knowl. Discov. Data, 2021

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

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

Redefining Neural Architecture Search of Heterogeneous Multi-Network Models by Characterizing Variation Operators and Model Components.
CoRR, 2021

On the Exploitation of Neuroevolutionary Information: Analyzing the Past for a More Efficient Future.
CoRR, 2021

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

Adversarial Perturbations for Evolutionary Optimization.
Proceedings of the Machine Learning, Optimization, and Data Science, 2021

Exploratory analysis of the Monte Carlo tree search for solving the linear ordering problem.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

On the exploitation of neuroevolutionary information.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Automatic Design of Deep Neural Networks Applied to Image Segmentation Problems.
Proceedings of the Genetic Programming - 24th European Conference, 2021

2020
Survey of Network Intrusion Detection Methods From the Perspective of the Knowledge Discovery in Databases Process.
IEEE Trans. Netw. Serv. Manag., 2020

Analysis of the transferability and robustness of GANs evolved for Pareto set approximations.
Neural Networks, 2020

EvoFlow: A Python library for evolving deep neural network architectures in tensorflow.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Automatic Structural Search for Multi-task Learning VALPs.
Proceedings of the Optimization and Learning - Third International Conference, 2020

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

A Symmetric grammar approach for designing segmentation models.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

Envisioning the Benefits of Back-Drive in Evolutionary Algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

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

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

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

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

Algorithm 989: perm_mateda: A Matlab Toolbox of Estimation of Distribution Algorithms for Permutation-based Combinatorial Optimization Problems.
ACM Trans. Math. Softw., 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

Towards a more efficient representation of imputation operators in TPOT.
CoRR, 2018

Expanding variational autoencoders for learning and exploiting latent representations in search distributions.
Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Evolved GANs for generating pareto set approximations.
Proceedings of the Genetic and Evolutionary Computation Conference, 2018

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

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

Analysis of the Complexity of the Automatic Pipeline Generation Problem.
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
Multiobjective decomposition-based Mallows Models estimation of distribution algorithm. A case of study for permutation flowshop scheduling problem.
Inf. Sci., 2017

A decomposition-based binary ACO algorithm for the multiobjective UBQP.
Neurocomputing, 2017

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

Evolving imputation strategies for missing data in classification problems with TPOT.
CoRR, 2017

Not all PBILs are the same: Unveiling the different learning mechanisms of PBIL variants.
Appl. Soft Comput., 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

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

Kernel density estimation in accelerators - Implementation and performance evaluation.
J. Supercomput., 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

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

On the Design of Hard mUBQP Instances.
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 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
A Survey of Performance Modeling and Simulation Techniques for Accelerator-Based Computing.
IEEE Trans. Parallel Distributed Syst., 2015

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

Modeling the availability of Cassandra.
J. Parallel Distributed Comput., 2015

An efficient implementation of kernel density estimation for multi-core and many-core architectures.
Int. J. High Perform. Comput. Appl., 2015

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

Multi-objective environmental model evaluation by means of multidimensional kernel density estimators: Efficient and multi-core implementations.
Environ. Model. Softw., 2015

MOEA/D-GM: Using probabilistic graphical models in MOEA/D for solving combinatorial optimization problems.
CoRR, 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

Competition-based failure-aware scheduling for High-Throughput Computing systems on peer-to-peer networks.
Clust. Comput., 2015

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

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

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

Distributed Estimation of Distribution Algorithms for continuous optimization: How does the exchanged information influence their behavior?
Inf. Sci., 2014

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

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

2013
High throughput computing over peer-to-peer networks.
Future Gener. Comput. Syst., 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

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

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

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

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
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

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

Porting Estimation of Distribution Algorithms to the Cell Broadband Engine.
Parallel Comput., 2010

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

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

2009
Evaluating the cell broadband engine as a platform to run estimation of distribution algorithms.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

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

2007
Combining Bayesian classifiers and estimation of distribution algorithms for optimization in continuous domains.
Connect. Sci., 2007

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

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

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

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

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


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