Evolutionary Optimization of Compiler Flag Selection by Learning and Exploiting Flags Interactions. - Unai Garciarena; Roberto Santana 001 (GECCO (Companion), 2016)

Evolving imputation strategies for missing data in classification problems with TPOT. - Unai Garciarena; Roberto Santana 001; Alexander Mendiburu (CoRR, 2017)

An extensive analysis of the interaction between missing data types, imputation methods, and supervised classifiers. - Unai Garciarena; Roberto Santana 001 (Expert Syst. Appl., 2017)

Analysis of the Complexity of the Automatic Pipeline Generation Problem. - Unai Garciarena; Roberto Santana 001; Alexander Mendiburu (CEC, 2018)

Evolved GANs for generating pareto set approximations. - Unai Garciarena; Roberto Santana 001; Alexander Mendiburu (GECCO, 2018)

Expanding variational autoencoders for learning and exploiting latent representations in search distributions. - Unai Garciarena; Roberto Santana 001; Alexander Mendiburu (GECCO, 2018)

Towards a more efficient representation of imputation operators in TPOT. - Unai Garciarena; Alexander Mendiburu; Roberto Santana 001 (CoRR, 2018)

Envisioning the Benefits of Back-Drive in Evolutionary Algorithms. - Unai Garciarena; Alexander Mendiburu; Roberto Santana 001 (CEC, 2020)

Automatic Structural Search for Multi-task Learning VALPs. - Unai Garciarena; Alexander Mendiburu; Roberto Santana 001 (OLA, 2020)

EvoFlow: A Python library for evolving deep neural network architectures in tensorflow. - Unai Garciarena; Roberto Santana 001; Alexander Mendiburu (SSCI, 2020)

Analysis of the transferability and robustness of GANs evolved for Pareto set approximations. - Unai Garciarena; Alexander Mendiburu; Roberto Santana 001 (Neural Networks, 2020)

On the exploitation of neuroevolutionary information. - Unai Garciarena; Nuno Lourenço 002; Penousal Machado; Roberto Santana 001; Alexander Mendiburu (GECCO Companion, 2021)

Semantic Technologies Towards Missing Values Imputation. - Iker Esnaola-Gonzalez; Unai Garciarena; Jesús Bermúdez (IEA/AIE (1), 2021)

Adversarial Perturbations for Evolutionary Optimization. - Unai Garciarena; Jon Vadillo; Alexander Mendiburu; Roberto Santana 001 (LOD, 2021)

On the Exploitation of Neuroevolutionary Information: Analyzing the Past for a More Efficient Future. - Unai Garciarena; Nuno Lourenço 002; Penousal Machado; Roberto Santana 001; Alexander Mendiburu (CoRR, 2021)

Redefining Neural Architecture Search of Heterogeneous Multi-Network Models by Characterizing Variation Operators and Model Components. - Unai Garciarena; Roberto Santana 001; Alexander Mendiburu (CoRR, 2021)

Towards Automatic Construction of Multi-Network Models for Heterogeneous Multi-Task Learning. - Unai Garciarena; Alexander Mendiburu; Roberto Santana 001 (ACM Trans. Knowl. Discov. Data, 2021)

Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification. - Roberto Santana 001; Ivan Hidalgo-Cenalmor; Unai Garciarena; Alexander Mendiburu; José Antonio Lozano 001 (GECCO Companion, 2023)

Analyzing the interplay between transferable GANs and gradient optimizers. - Unai Garciarena; Roberto Santana 001; Alexander Mendiburu (GECCO Companion, 2023)

Factorized models in neural architecture search: Impact on computational costs and performance. - Unai Garciarena; Alexander Mendiburu; Roberto Santana 001 (IJCNN, 2024)

Redefining Neural Architecture Search of Heterogeneous Multinetwork Models by Characterizing Variation Operators and Model Components. - Unai Garciarena; Roberto Santana 001; Alexander Mendiburu (IEEE Trans. Neural Networks Learn. Syst., 2024)