Roberto Santana
Orcid: 0000-0002-1005-8535Affiliations:
- University of the Basque Country, San Sebastián - Donostia, Spain
According to our database1,
Roberto Santana
authored at least 179 papers
between 2000 and 2025.
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Bibliography
2025
Adversarial Attacks in Explainable Machine Learning: A Survey of Threats Against Models and Humans.
WIREs Data. Mining. Knowl. Discov., March, 2025
Leveraging constraint programming in a deep learning approach for dynamically solving the flexible job-shop scheduling problem.
Expert Syst. Appl., 2025
Diverse policy generation for the flexible job-shop scheduling problem via deep reinforcement learning with a novel graph representation.
Eng. Appl. Artif. Intell., 2025
2024
ACM Trans. Evol. Learn. Optim., December, 2024
On the generalization of PINNs outside the training domain and the hyperparameters influencing it.
Neural Comput. Appl., December, 2024
Redefining Neural Architecture Search of Heterogeneous Multinetwork Models by Characterizing Variation Operators and Model Components.
IEEE Trans. Neural Networks Learn. Syst., August, 2024
Computational Tools for Neuronal Morphometric Analysis: A Systematic Search and Review.
Neuroinformatics, July, 2024
Unified Framework for the Analysis of the Effect of Control Strategies on On-Load Tap-Changer's Automatic Voltage Controller.
IEEE Trans Autom. Sci. Eng., April, 2024
Filter method-based feature selection process for unattributed-identity multi-target regression problem.
Expert Syst. Appl., 2024
Eur. J. Oper. Res., 2024
Domain Adaptation-Enhanced Searchlight: Enabling brain decoding from visual perception to mental imagery.
CoRR, 2024
Identifying phase transitions in physical systems with neural networks: a neural architecture search perspective.
CoRR, 2024
Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks.
CoRR, 2024
Proceedings of the Seminar of the Spanish Society for Natural Language Processing: Projects and System Demonstrations (SEPLN-CEDI-PD 2024) co-located with the 7th Spanish Conference on Informatics (CEDI 2024), 2024
Multi-Assignment Scheduler: A New Behavioral Cloning Method for the Job-Shop Scheduling Problem.
Proceedings of the Learning and Intelligent Optimization - 18th International Conference, 2024
Factorized models in neural architecture search: Impact on computational costs and performance.
Proceedings of the International Joint Conference on Neural Networks, 2024
Continuous estimation of distribution algorithms for the parametric optimization of geothermal power plants.
Proceedings of the 7th International Conference on Computational Intelligence and Intelligent Systems, 2024
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
Solving large flexible job shop scheduling instances by generating a diverse set of scheduling policies with deep reinforcement learning.
CoRR, 2023
CoRR, 2023
On the Hyperparameters influencing a PINN's generalization beyond the training domain.
CoRR, 2023
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023
The Impact of Imputation Methods on the Classification of Household Devices from Electricity Usage Time Series.
Proceedings of the Tenth International Conference on Social Networks Analysis, 2023
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
Knowl. Based Syst., 2022
Solving the multi-objective Hamiltonian cycle problem using a Branch-and-Fix based algorithm.
J. Comput. Sci., 2022
Genet. Program. Evolvable Mach., 2022
Comput. Secur., 2022
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022
2021
Towards Automatic Construction of Multi-Network Models for Heterogeneous Multi-Task Learning.
ACM Trans. Knowl. Discov. Data, 2021
Neural Comput. Appl., 2021
Estimation of distribution algorithms for the computation of innovation estimators of diffusion processes.
Math. Comput. Simul., 2021
Evolving Gaussian process kernels from elementary mathematical expressions for time series extrapolation.
Neurocomputing, 2021
Analysis of Bayesian Network Learning Techniques for a Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm: a case study on MNK Landscape.
J. Heuristics, 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
CoRR, 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
Proceedings of the Machine Learning, Optimization, and Data Science, 2021
Proceedings of the ICMI '21: International Conference on Multimodal Interaction, 2021
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
Proceedings of the Genetic Programming - 24th European Conference, 2021
2020
Analysis of the transferability and robustness of GANs evolved for Pareto set approximations.
Neural Networks, 2020
Tool-Path Problem in Direct Energy Deposition Metal-Additive Manufacturing: Sequence Strategy Generation.
IEEE Access, 2020
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020
EvoFlow: A Python library for evolving deep neural network architectures in tensorflow.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020
Proceedings of the Optimization and Learning - Third International Conference, 2020
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
Proceedings of the IEEE Congress on Evolutionary Computation, 2020
Proceedings of the IEEE Congress on Evolutionary Computation, 2020
Proceedings of the IEEE Congress on Evolutionary Computation, 2020
2019
Multimodal Technol. Interact., 2019
Knowl. Based Syst., 2019
GP-based methods for domain adaptation: using brain decoding across subjects as a test-case.
Genet. Program. Evolvable Mach., 2019
CoRR, 2019
IEEE Access, 2019
Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, 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
Adaptation of a Branching Algorithm to Solve the Multi-Objective Hamiltonian Cycle Problem.
Proceedings of the Operations Research Proceedings 2019, 2019
Proceedings of the Learning and Intelligent Optimization - 13th International Conference, 2019
Proceedings of the Learning and Intelligent Optimization - 13th International Conference, 2019
Proceedings of the Genetic and Evolutionary Computation Conference, 2019
Optimizing permutation-based problems with a discrete vine-copula as a model for EDA.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019
Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019
2018
Algorithm 989: perm_mateda: A Matlab Toolbox of Estimation of Distribution Algorithms for Permutation-based Combinatorial Optimization Problems.
ACM Trans. Math. Softw., 2018
Hybrid multi-objective Bayesian estimation of distribution algorithm: a comparative analysis for the multi-objective knapsack problem.
J. Heuristics, 2018
Appl. Soft Comput., 2018
Exploring the probabilistic graphic model of a hybrid multi-objective Bayesian estimation of distribution algorithm.
Appl. Soft Comput., 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
EMPATHIC, Expressive, Advanced Virtual Coach to Improve Independent Healthy-Life-Years of the Elderdy.
Proceedings of the Fourth International Conference, 2018
Expanding variational autoencoders for learning and exploiting latent representations in search distributions.
Proceedings of the Genetic and Evolutionary Computation Conference, 2018
Proceedings of the Genetic and Evolutionary Computation Conference, 2018
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018
On the Performance of Multi-Objective Estimation of Distribution Algorithms for Combinatorial Problems.
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018
2017
An investigation of clustering strategies in many-objective optimization: the I-Multi algorithm as a case study.
Swarm Intell., 2017
Transfer weight functions for injecting problem information in the multi-objective CMA-ES.
Memetic Comput., 2017
Multiobjective decomposition-based Mallows Models estimation of distribution algorithm. A case of study for permutation flowshop scheduling problem.
Inf. Sci., 2017
Neurocomputing, 2017
An extensive analysis of the interaction between missing data types, imputation methods, and supervised classifiers.
Expert Syst. Appl., 2017
Gray-box optimization and factorized distribution algorithms: where two worlds collide.
CoRR, 2017
Reproducing and learning new algebraic operations on word embeddings using genetic programming.
CoRR, 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
Proceedings of the Genetic and Evolutionary Computation Conference, 2017
A comparison of probabilistic-based optimization approaches for vehicle routing problems.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017
Automated design of hyper-heuristics components to solve the PSP problem with HP model.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017
Probabilistic Analysis of Pareto Front Approximation for a Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm.
Proceedings of the 2017 Brazilian Conference on Intelligent Systems, 2017
2016
Nat. Comput., 2016
Neurocomputing, 2016
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016
Evolutionary Optimization of Compiler Flag Selection by Learning and Exploiting Flags Interactions.
Proceedings of the Genetic and Evolutionary Computation Conference, 2016
Maximal nonlinearity in balanced boolean functions with even number of inputs, revisited.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016
Investigating Selection Strategies in Multi-objective Probabilistic Model Based Algorithms.
Proceedings of the 5th Brazilian Conference on Intelligent Systems, 2016
2015
Comprehensive characterization of the behaviors of estimation of distribution algorithms.
Theor. Comput. Sci., 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
Appl. Soft Comput., 2015
Proceedings of the Genetic and Evolutionary Computation Conference, 2015
Proceedings of the Genetic and Evolutionary Computation Conference, 2015
Proceedings of the IEEE Congress on Evolutionary Computation, 2015
Proceedings of the IEEE Congress on Evolutionary Computation, 2015
Proceedings of the 2015 Brazilian Conference on Intelligent Systems, 2015
2014
Multiobjective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables.
IEEE Trans. Evol. Comput., 2014
Proceedings of the Simulated Evolution and Learning - 10th International Conference, 2014
Proceedings of the Simulated Evolution and Learning - 10th International Conference, 2014
2013
A review on evolutionary algorithms in Bayesian network learning and inference tasks.
Inf. Sci., 2013
Int. J. Comput. Intell. Syst., 2013
On the Taxonomy of Optimization Problems Under Estimation of Distribution Algorithms.
Evol. Comput., 2013
Appl. Soft 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
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
J. Heuristics, 2012
Regularized logistic regression and multiobjective variable selection for classifying MEG data.
Biol. Cybern., 2012
Proceedings of the Genetic and Evolutionary Computation Conference, 2012
Introducing the use of model-based evolutionary algorithms for EEG-based motor imagery classification.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012
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
Neuroinformatics, 2011
Univariate marginal distribution algorithm dynamics for a class of parametric functions with unitation constraints.
Inf. Sci., 2011
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011
Quantitative genetics in multi-objective optimization algorithms: from useful insights to effective methods.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011
Estimation of distribution algorithms: from available implementations to potential developments.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011
Multi-objective Optimization with Joint Probabilistic Modeling of Objectives and Variables.
Proceedings of the Evolutionary Multi-Criterion Optimization, 2011
Proceedings of the IEEE Congress on Evolutionary Computation, 2011
Proceedings of the IEEE Congress on Evolutionary Computation, 2011
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
Synergies between Network-Based Representation and Probabilistic Graphical Models for Classification, Inference and Optimization Problems in Neuroscience.
Proceedings of the Trends in Applied Intelligent Systems, 2010
Using Probabilistic Dependencies Improves the Search of Conductance-Based Compartmental Neuron Models.
Proceedings of the Evolutionary Computation, 2010
Proceedings of the IEEE Congress on Evolutionary Computation, 2010
Bivariate empirical and n-variate Archimedean copulas in estimation of distribution algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010
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
Proceedings of the IEEE Congress on Evolutionary Computation, 2009
2008
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
IEEE Trans. Evol. Comput., 2008
Combining variable neighborhood search and estimation of distribution algorithms in the protein side chain placement problem.
J. Heuristics, 2008
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
Proceedings of the Genetic and Evolutionary Computation Conference, 2008
Proceedings of the IEEE Congress on Evolutionary Computation, 2008
2007
Artif. Intell. Medicine, 2007
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
Proceedings of the IEEE Congress on Evolutionary Computation, 2007
2006
Proceedings of the Machine Learning: ECML 2006, 2006
2005
Evol. Comput., 2005
Proceedings of the IEEE Congress on Evolutionary Computation, 2005
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
Proceedings of the Machine Learning: ECML 2003, 2003
2002
Proceedings of the 2002 Congress on Evolutionary Computation, 2002
2001
Electron. Notes Discret. Math., 2001
2000
Probabilistic Evolution and the Busy Beaver Problem.
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '00), 2000
Too busy to learn [individual learning interaction with evolutionary algorithm in Busy Beaver problem].
Proceedings of the 2000 Congress on Evolutionary Computation, 2000