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ORCIDJavier Poyatos
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2020 – today
- 2024
[j6]Isaac Triguero
, Daniel Molina, Javier Poyatos, Javier Del Ser, Francisco Herrera:
General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance. Inf. Fusion 103: 102135 (2024)- [i6]Javier Poyatos, Javier Del Ser, Salvador García, Hisao Ishibuchi, Daniel Molina, Isaac Triguero, Bing Xue, Xin Yao, Francisco Herrera:
Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospects. CoRR abs/2407.08745 (2024) - 2023
- [j5]Javier Poyatos, Daniel Molina, Aitor Martínez-Seras, Javier Del Ser, Francisco Herrera:
Multiobjective evolutionary pruning of Deep Neural Networks with Transfer Learning for improving their performance and robustness. Appl. Soft Comput. 147: 110757 (2023) - [j4]Javier Poyatos, Daniel Molina, Aritz D. Martinez, Javier Del Ser, Francisco Herrera:
EvoPruneDeepTL: An evolutionary pruning model for transfer learning based deep neural networks. Neural Networks 158: 59-82 (2023) - [i5]Javier Poyatos, Daniel Molina, Aitor Martínez-Seras, Javier Del Ser, Francisco Herrera:
Multiobjective Evolutionary Pruning of Deep Neural Networks with Transfer Learning for improving their Performance and Robustness. CoRR abs/2302.10253 (2023) - [i4]Isaac Triguero, Daniel Molina, Javier Poyatos, Javier Del Ser, Francisco Herrera:
General Purpose Artificial Intelligence Systems (GPAIS): Properties, Definition, Taxonomy, Open Challenges and Implications. CoRR abs/2307.14283 (2023) - 2022
- [i3]Javier Poyatos, Daniel Molina, Aritz D. Martinez, Javier Del Ser, Francisco Herrera:
EvoPruneDeepTL: An Evolutionary Pruning Model for Transfer Learning based Deep Neural Networks. CoRR abs/2202.03844 (2022) - 2021
- [j3]Aritz D. Martinez, Javier Del Ser, Esther Villar-Rodriguez, Eneko Osaba, Javier Poyatos, Siham Tabik, Daniel Molina, Francisco Herrera:
Lights and shadows in Evolutionary Deep Learning: Taxonomy, critical methodological analysis, cases of study, learned lessons, recommendations and challenges. Inf. Fusion 67: 161-194 (2021) - [j2]Antonio LaTorre, Daniel Molina, Eneko Osaba, Javier Poyatos, Javier Del Ser, Francisco Herrera:
A prescription of methodological guidelines for comparing bio-inspired optimization algorithms. Swarm Evol. Comput. 67: 100973 (2021) - [c1]Javier Del Ser, Eneko Osaba, Aritz D. Martinez, Miren Nekane Bilbao, Javier Poyatos, Daniel Molina, Francisco Herrera:
More is not Always Better: Insights from a Massive Comparison of Meta-heuristic Algorithms over Real-Parameter Optimization Problems. SSCI 2021: 1-7 - 2020
- [j1]Daniel Molina, Javier Poyatos, Javier Del Ser, Salvador García, Amir Hussain, Francisco Herrera:
Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration Versus Algorithmic Behavior, Critical Analysis Recommendations. Cogn. Comput. 12(5): 897-939 (2020) - [i2]Daniel Molina, Javier Poyatos, Javier Del Ser, Salvador García, Amir Hussain, Francisco Herrera:
Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration versus Algorithmic Behavior, Critical Analysis and Recommendations. CoRR abs/2002.08136 (2020) - [i1]Aritz D. Martinez, Javier Del Ser, Esther Villar-Rodriguez, Eneko Osaba, Javier Poyatos, Siham Tabik, Daniel Molina, Francisco Herrera:
Lights and Shadows in Evolutionary Deep Learning: Taxonomy, Critical Methodological Analysis, Cases of Study, Learned Lessons, Recommendations and Challenges. CoRR abs/2008.03620 (2020)
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