Roberto Santana

Orcid: 0000-0002-1005-8535

Affiliations:
  • University of the Basque Country, San Sebastián - Donostia, Spain


According to our database1, Roberto Santana authored at least 159 papers between 2000 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

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

Structural Restricted Boltzmann Machine for image denoising and classification.
CoRR, 2023

On the Hyperparameters influencing a PINN's generalization beyond the training domain.
CoRR, 2023

Evolved Neural Networks for Building Energy Prediction.
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

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

Solving the multi-objective Hamiltonian cycle problem using a Branch-and-Fix based algorithm.
J. Comput. Sci., 2022

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

On the human evaluation of universal audio adversarial perturbations.
Comput. Secur., 2022

Evolutionary approaches with adaptive operators for the bi-objective TTP.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Boomerang-shaped neural embeddings for NK landscapes.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

Multi-objective NK landscapes with heterogeneous objectives.
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

In-depth analysis of SVM kernel learning and its components.
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

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

Adversarial Perturbations for Evolutionary Optimization.
Proceedings of the Machine Learning, Optimization, and Data Science, 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
Analysis of the transferability and robustness of GANs evolved for Pareto set approximations.
Neural Networks, 2020

On the human evaluation of audio adversarial examples.
CoRR, 2020

Tool-Path Problem in Direct Energy Deposition Metal-Additive Manufacturing: Sequence Strategy Generation.
IEEE Access, 2020

Investigating RNNs for vehicle volume forecasting in service stations.
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

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

Dynamic programming operators for the bi-objective Traveling Thief Problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 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
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

GP-based methods for domain adaptation: using brain decoding across subjects as a test-case.
Genet. Program. Evolvable Mach., 2019

Universal adversarial examples in speech command classification.
CoRR, 2019

Evolving Gaussian Process kernels from elementary mathematical expressions.
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

Adaptation of a Branching Algorithm to Solve the Multi-Objective Hamiltonian Cycle Problem.
Proceedings of the Operations Research Proceedings 2019, 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

Optimizing permutation-based problems with a discrete vine-copula as a model for EDA.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019

Automatic Design of Convolutional Neural Networks using Grammatical Evolution.
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

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

An investigation of the selection strategies impact on MOEDAs: CMA-ES and UMDA.
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

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

Modeling dependencies between decision variables and objectives with copula models.
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

Analysis of the Complexity of the Automatic Pipeline Generation Problem.
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

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

Different scenarios for survival analysis of evolutionary algorithms.
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

Combining CMA-ES and MOEA/DD for many-objective optimization.
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
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

C-Multi: A competent multi-swarm approach for many-objective problems.
Neurocomputing, 2016

On the Design of Hard mUBQP Instances.
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016

Evolutionary Approaches to Optimization Problems in Chimera Topologies.
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20, 2016

HMOBEDA: Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm.
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

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

Fighting the Symmetries: The Structure of Cryptographic Boolean Function Spaces.
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

Capturing Relationships in Multi-objective Optimization.
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

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

A Probabilistic Evolutionary Optimization Approach to Compute Quasiparticle Braids.
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

Network measures for information extraction in evolutionary algorithms.
Int. J. Comput. Intell. Syst., 2013

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

Regularized continuous estimation of distribution algorithms.
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

Symmetry in evolutionary and estimation of distribution algorithms.
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 probabilistic graphical models in evolutionary computation.
J. Heuristics, 2012

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

Regularized logistic regression and multiobjective variable selection for classifying MEG data.
Biol. Cybern., 2012

Evolving NK-complexity for evolutionary solvers.
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

Maximizing the number of polychronous groups in spiking networks.
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
Optimizing Brain Networks Topologies Using Multi-objective Evolutionary Computation.
Neuroinformatics, 2011

Univariate marginal distribution algorithm dynamics for a class of parametric functions with unitation constraints.
Inf. Sci., 2011

A direct optimization approach to the P300 speller.
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

Regularized k-order markov models in EDAs.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Affinity propagation enhanced by estimation of distribution algorithms.
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

A differential evolution algorithm for the detection of synaptic vesicles.
Proceedings of the IEEE Congress on Evolutionary Computation, 2011

On the limits of effectiveness in estimation of distribution algorithms.
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

Estimation of Bayesian networks algorithms in a class of complex networks.
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

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

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

An EDA based on local markov property and gibbs sampling.
Proceedings of the Genetic and Evolutionary Computation Conference, 2008

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

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

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

2006
Machine learning in bioinformatics.
Briefings Bioinform., 2006

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

2005
Estimation of Distribution Algorithms with Kikuchi Approximations.
Evol. Comput., 2005

Interactions and dependencies in estimation of distribution algorithms.
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
A Markov Network Based Factorized Distribution Algorithm for Optimization.
Proceedings of the Machine Learning: ECML 2003, 2003

2002
Blocked stochastic sampling versus Estimation of Distribution Algorithms.
Proceedings of the 2002 Congress on Evolutionary Computation, 2002

2001
On the use of Factorized Distribution Algorithms for problems defined on graphs.
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


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