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Unai Garciarena
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2020 – today
- 2024
- [j4]Unai Garciarena
, Roberto Santana
Redefining Neural Architecture Search of Heterogeneous Multinetwork Models by Characterizing Variation Operators and Model Components. IEEE Trans. Neural Networks Learn. Syst. 35(8): 10561-10575 (2024) - [c13]Unai Garciarena, Alexander Mendiburu, Roberto Santana:
Factorized models in neural architecture search: Impact on computational costs and performance. IJCNN 2024: 1-8 - 2023
- [c12]Roberto Santana
Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification. GECCO Companion 2023: 679-682 - [c11]Unai Garciarena
Analyzing the interplay between transferable GANs and gradient optimizers. GECCO Companion 2023: 1777-1784 - [i6]Roberto Santana, Ivan Hidalgo-Cenalmor, Unai Garciarena, Alexander Mendiburu, José Antonio Lozano:
Neuroevolutionary algorithms driven by neuron coverage metrics for semi-supervised classification. CoRR abs/2303.02801 (2023) - 2021
- [j3]Unai Garciarena
Towards Automatic Construction of Multi-Network Models for Heterogeneous Multi-Task Learning. ACM Trans. Knowl. Discov. Data 15(2): 33:1-33:23 (2021) - [c10]Unai Garciarena, Nuno Lourenço
On the exploitation of neuroevolutionary information. GECCO Companion 2021: 279-280 - [c9]Iker Esnaola-Gonzalez
Semantic Technologies Towards Missing Values Imputation. IEA/AIE (1) 2021: 191-196 - [c8]Unai Garciarena
Adversarial Perturbations for Evolutionary Optimization. LOD 2021: 408-422 - [i5]Unai Garciarena, Nuno Lourenço, Penousal Machado, Roberto Santana, Alexander Mendiburu:
On the Exploitation of Neuroevolutionary Information: Analyzing the Past for a More Efficient Future. CoRR abs/2105.12836 (2021) - [i4]Unai Garciarena, Roberto Santana, Alexander Mendiburu:
Redefining Neural Architecture Search of Heterogeneous Multi-Network Models by Characterizing Variation Operators and Model Components. CoRR abs/2106.08972 (2021) - 2020
- [j2]Unai Garciarena
Analysis of the transferability and robustness of GANs evolved for Pareto set approximations. Neural Networks 132: 281-296 (2020) - [c7]Unai Garciarena
Envisioning the Benefits of Back-Drive in Evolutionary Algorithms. CEC 2020: 1-8 - [c6]Unai Garciarena
Automatic Structural Search for Multi-task Learning VALPs. OLA 2020: 25-36 - [c5]Unai Garciarena, Roberto Santana, Alexander Mendiburu
EvoFlow: A Python library for evolving deep neural network architectures in tensorflow. SSCI 2020: 2288-2295
2010 – 2019
- 2019
- [i3]Unai Garciarena, Alexander Mendiburu, Roberto Santana:
Towards automatic construction of multi-network models for heterogeneous multi-task learning. CoRR abs/1903.09171 (2019) - 2018
- [c4]Unai Garciarena
Analysis of the Complexity of the Automatic Pipeline Generation Problem. CEC 2018: 1-8 - [c3]Unai Garciarena
Evolved GANs for generating pareto set approximations. GECCO 2018: 434-441 - [c2]Unai Garciarena
Expanding variational autoencoders for learning and exploiting latent representations in search distributions. GECCO 2018: 849-856 - [i2]Unai Garciarena, Alexander Mendiburu, Roberto Santana:
Towards a more efficient representation of imputation operators in TPOT. CoRR abs/1801.04407 (2018) - 2017
- [j1]Unai Garciarena
An extensive analysis of the interaction between missing data types, imputation methods, and supervised classifiers. Expert Syst. Appl. 89: 52-65 (2017) - [i1]Unai Garciarena, Roberto Santana, Alexander Mendiburu:
Evolving imputation strategies for missing data in classification problems with TPOT. CoRR abs/1706.01120 (2017) - 2016
- [c1]Unai Garciarena
Evolutionary Optimization of Compiler Flag Selection by Learning and Exploiting Flags Interactions. GECCO (Companion) 2016: 1159-1166
Coauthor Index
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