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Javier Poyatos
Javier Poyatos
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Comprehensive taxonomies of nature-and bio-inspired optimization: Inspiration versus algorithmic behavior, critical analysis recommendations
D Molina, J Poyatos, JD Ser, S García, A Hussain, F Herrera
Cognitive Computation 12, 897-939, 2020
1972020
A prescription of methodological guidelines for comparing bio-inspired optimization algorithms
A LaTorre, D Molina, E Osaba, J Poyatos, J Del Ser, F Herrera
Swarm and Evolutionary Computation 67, 100973, 2021
852021
Lights and shadows in Evolutionary Deep Learning: Taxonomy, critical methodological analysis, cases of study, learned lessons, recommendations and challenges
AD Martinez, J Del Ser, E Villar-Rodriguez, E Osaba, J Poyatos, S Tabik, ...
Information Fusion 67, 161-194, 2021
392021
EvoPruneDeepTL: An evolutionary pruning model for transfer learning based deep neural networks
J Poyatos, D Molina, AD Martinez, J Del Ser, F Herrera
Neural Networks 158, 59-82, 2023
212023
More is not always better: Insights from a massive comparison of meta-heuristic algorithms over real-parameter optimization problems
J Del Ser, E Osaba, AD Martinez, MN Bilbao, J Poyatos, D Molina, ...
2021 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2021
82021
General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance
I Triguero, D Molina, J Poyatos, J Del Ser, F Herrera
Information Fusion 103, 102135, 2024
52024
Multiobjective evolutionary pruning of Deep Neural Networks with Transfer Learning for improving their performance and robustness
J Poyatos, D Molina, A Martínez-Seras, J Del Ser, F Herrera
Applied Soft Computing 147, 110757, 2023
42023
General Purpose Artificial Intelligence Systems (GPAIS): Properties, Definition, Taxonomy, Open Challenges and Implications
I Triguero, D Molina, J Poyatos, J Del Ser, F Herrera
arXiv preprint arXiv:2307.14283, 2023
32023
Nature-and bio-inspired optimization: The good, the bad, the ugly and the hopeful
D Molina Cabrera, J POYATOS AMADOR, E OSABA ICEDO, ...
DYNA Ingeniería e Industria, 2022
22022
EvoPruneDeepTL: An evolutionary pruning model for transfer learning based deep neural networks
J Poyatos Amador, D Molina Cabrera, AD Martínez, J Del Ser, ...
2023
Multiobjective evolutionary pruning of Deep Neural Networks with Transfer Learning for improving their performance and robustness
J Poyatos Amador, D Molina Cabrera, A Martínez-Seras, J Del Ser, ...
2023
Optimización inspirada en la naturaleza y en la biología: lo bueno, lo malo, lo feo y lo esperanzador
DM Cabrera, J Poyatos, E Osaba, J DEL SER, F HERRERA
DYNA 97 (2), 114-117, 2022
2022
Comprehensive Taxonomies of Nature-and Bio-inspired Optimization: Inspiration Versus Algorithmic Behavior, Critical Analysis Recommendations
D Molina Cabrera, J Poyatos Amador, J Del Ser, S García López, ...
2020
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