An extensive analysis of the interaction between missing data types, imputation methods, and supervised classifiers U Garciarena, R Santana Expert Systems with Applications 89, 52-65, 2017 | 139 | 2017 |
Evolved GANs for generating Pareto set approximations U Garciarena, R Santana, A Mendiburu Proceedings of the genetic and evolutionary computation conference, 434-441, 2018 | 48 | 2018 |
Evolutionary optimization of compiler flag selection by learning and exploiting flags interactions U Garciarena, R Santana Proceedings of the 2016 on Genetic and Evolutionary Computation Conference …, 2016 | 37 | 2016 |
Analysis of the Complexity of the Automatic Pipeline Generation Problem U Garciarena, R Santana, A Mendiburu 2018 IEEE Congress on Evolutionary Computation (CEC), 1841-1848, 2018 | 22 | 2018 |
Expanding variational autoencoders for learning and exploiting latent representations in search distributions U Garciarena, R Santana, A Mendiburu Proceedings of the Genetic and Evolutionary Computation Conference, 849-856, 2018 | 19 | 2018 |
Analysis of the transferability and robustness of GANs evolved for Pareto set approximations U Garciarena, A Mendiburu, R Santana Neural Networks 132, 281-296, 2020 | 14 | 2020 |
Evolving imputation strategies for missing data in classification problems with TPOT U Garciarena, R Santana, A Mendiburu arXiv preprint arXiv:1706.01120, 2017 | 12 | 2017 |
EvoFlow: A Python library for evolving deep neural network architectures in tensorflow U Garciarena, R Santana, A Mendiburu 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2288-2295, 2020 | 6 | 2020 |
An investigation of imputation methods for discrete databases and multi-variate time series U Garciarena M. Sci. Thesis University of the Basque Country, Spain, 2016 | 6 | 2016 |
Towards a more efficient representation of imputation operators in TPOT U Garciarena, A Mendiburu, R Santana arXiv preprint arXiv:1801.04407, 2018 | 5 | 2018 |
Towards automatic construction of multi-network models for heterogeneous multi-task learning U Garciarena, A Mendiburu, R Santana ACM Transactions on Knowledge Discovery from Data (TKDD) 15 (2), 1-23, 2021 | 4 | 2021 |
Adversarial perturbations for evolutionary optimization U Garciarena, J Vadillo, A Mendiburu, R Santana International Conference on Machine Learning, Optimization, and Data Science …, 2021 | 3 | 2021 |
On the exploitation of neuroevolutionary information U Garciarena, N Lourenço, P Machado, R Santana, A Mendiburu Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021 | 3 | 2021 |
Envisioning the benefits of back-drive in evolutionary algorithms U Garciarena, A Mendiburu, R Santana 2020 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2020 | 3 | 2020 |
Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification R Santana, I Hidago-Cenalmor, U Garciarena, A Mendiburu, JA Lozano Proceedings of the Companion Conference on Genetic and Evolutionary …, 2023 | 2 | 2023 |
Redefining Neural Architecture Search of Heterogeneous Multinetwork Models by Characterizing Variation Operators and Model Components U Garciarena, R Santana, A Mendiburu IEEE Transactions on Neural Networks and Learning Systems, 2023 | 2 | 2023 |
Semantic Technologies Towards Missing Values Imputation I Esnaola-Gonzalez, U Garciarena, J Bermúdez Advances and Trends in Artificial Intelligence. Artificial Intelligence …, 2021 | 2 | 2021 |
Automatic Structural Search for Multi-task Learning VALPs U Garciarena, A Mendiburu, R Santana International Conference on Optimization and Learning, 25-36, 2020 | 2 | 2020 |
On the Exploitation of Neuroevolutionary Information: Analyzing the Past for a More Efficient Future U Garciarena, N Lourenço, P Machado, R Santana, A Mendiburu arXiv preprint arXiv:2105.12836, 2021 | 1 | 2021 |
Factorized models in neural architecture search: Impact on computational costs and performance U Garciarena, A Mendiburu, R Santana 2024 International Joint Conference on Neural Networks (IJCNN), 1-8, 2024 | | 2024 |