Unai Garciarena

IEEE Trans. Neural Networks Learn. Syst., August, 2024

Factorized models in neural architecture search: Impact on computational costs and performance.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

Analyzing the interplay between transferable GANs and gradient optimizers.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Ivan Hidalgo-Cenalmor

José Antonio Lozano

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2021

Towards Automatic Construction of Multi-Network Models for Heterogeneous Multi-Task Learning.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

CoRR, 2021

Adversarial Perturbations for Evolutionary Optimization.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, Optimization, and Data Science, 2021

Semantic Technologies Towards Missing Values Imputation.

[BibT_eX]

[DOI]

Iker Esnaola-Gonzalez

Jesús Bermúdez

Proceedings of the Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices, 2021

On the exploitation of neuroevolutionary information.

[BibT_eX]

[DOI]

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2020

Analysis of the transferability and robustness of GANs evolved for Pareto set approximations.

[BibT_eX]

[DOI]

Neural Networks, 2020

EvoFlow: A Python library for evolving deep neural network architectures in tensorflow.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Automatic Structural Search for Multi-task Learning VALPs.

[BibT_eX]

[DOI]

Proceedings of the Optimization and Learning - Third International Conference, 2020

Envisioning the Benefits of Back-Drive in Evolutionary Algorithms.

[BibT_eX]

[DOI]

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2018

Towards a more efficient representation of imputation operators in TPOT.

[BibT_eX]

[DOI]

CoRR, 2018

Expanding variational autoencoders for learning and exploiting latent representations in search distributions.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Evolved GANs for generating pareto set approximations.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Analysis of the Complexity of the Automatic Pipeline Generation Problem.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

2017

An extensive analysis of the interaction between missing data types, imputation methods, and supervised classifiers.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2017

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

[BibT_eX]

[DOI]

CoRR, 2017

2016

Evolutionary Optimization of Compiler Flag Selection by Learning and Exploiting Flags Interactions.

[BibT_eX]

[DOI]