Javier Poyatos

15 papers Journal 14Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
The Paradox of Success in Evolutionary and Bioinspired Optimization: Revisiting Critical Issues, Key Studies, and Methodological Pathways.
CoRR
Daniel Molina, Javier Del Ser, Javier Poyatos, Francisco Herrera
2025 J jnl
The paradox of success in evolutionary and bioinspired optimization: Revisiting critical issues, key studies, and methodological pathways.
Swarm Evol. Comput.
Daniel Molina, Javier Del Ser, Javier Poyatos, Francisco Herrera
2024 J jnl
Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospects.
CoRR
Javier Poyatos, Javier Del Ser, Salvador García, Hisao Ishibuchi, Daniel Molina, Isaac Triguero, Bing Xue, Xin Yao, Francisco Herrera
2024 J jnl
General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance.
Inf. Fusion
Isaac Triguero, Daniel Molina, Javier Poyatos, Javier Del Ser, Francisco Herrera
2023 J jnl
EvoPruneDeepTL: An evolutionary pruning model for transfer learning based deep neural networks.
Neural Networks
Javier Poyatos, Daniel Molina, Aritz D. Martinez, Javier Del Ser, Francisco Herrera
2023 J jnl
General Purpose Artificial Intelligence Systems (GPAIS): Properties, Definition, Taxonomy, Open Challenges and Implications.
CoRR
Isaac Triguero, Daniel Molina, Javier Poyatos, Javier Del Ser, Francisco Herrera
2023 J jnl
Multiobjective Evolutionary Pruning of Deep Neural Networks with Transfer Learning for improving their Performance and Robustness.
CoRR
Javier Poyatos, Daniel Molina, Aitor Martínez-Seras, Javier Del Ser, Francisco Herrera
2023 J jnl
Multiobjective evolutionary pruning of Deep Neural Networks with Transfer Learning for improving their performance and robustness.
Appl. Soft Comput.
Javier Poyatos, Daniel Molina, Aitor Martínez-Seras, Javier Del Ser, Francisco Herrera
2022 J jnl
EvoPruneDeepTL: An Evolutionary Pruning Model for Transfer Learning based Deep Neural Networks.
CoRR
Javier Poyatos, Daniel Molina, Aritz D. Martinez, Javier Del Ser, Francisco Herrera
2021 J jnl
A prescription of methodological guidelines for comparing bio-inspired optimization algorithms.
Swarm Evol. Comput.
Antonio LaTorre, Daniel Molina, Eneko Osaba, Javier Poyatos, Javier Del Ser, Francisco Herrera
2021 J jnl
Lights and shadows in Evolutionary Deep Learning: Taxonomy, critical methodological analysis, cases of study, learned lessons, recommendations and challenges.
Inf. Fusion
Aritz D. Martinez, Javier Del Ser, Esther Villar-Rodriguez, Eneko Osaba, Javier Poyatos, Siham Tabik, Daniel Molina, Francisco Herrera
2021 — conf
More is not Always Better: Insights from a Massive Comparison of Meta-heuristic Algorithms over Real-Parameter Optimization Problems.
SSCI
Javier Del Ser, Eneko Osaba, Aritz D. Martinez, Miren Nekane Bilbao, Javier Poyatos, Daniel Molina, Francisco Herrera
2020 J jnl
Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration Versus Algorithmic Behavior, Critical Analysis Recommendations.
Cogn. Comput.
Daniel Molina, Javier Poyatos, Javier Del Ser, Salvador García, Amir Hussain, Francisco Herrera
2020 J jnl
Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration versus Algorithmic Behavior, Critical Analysis and Recommendations.
CoRR
Daniel Molina, Javier Poyatos, Javier Del Ser, Salvador García, Amir Hussain, Francisco Herrera
2020 J jnl
Lights and Shadows in Evolutionary Deep Learning: Taxonomy, Critical Methodological Analysis, Cases of Study, Learned Lessons, Recommendations and Challenges.
CoRR
Aritz D. Martinez, Javier Del Ser, Esther Villar-Rodriguez, Eneko Osaba, Javier Poyatos, Siham Tabik, Daniel Molina, Francisco Herrera