Javier Poyatos

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 13

Top Topics

Transfer Learning

Optimization Problems

Evolutionary Computation

Top Venues

Swarm Evol. Comput.

Publications

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 (2024)
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 (2024)
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 (2023)
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 (2023)
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 (2023)
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 (2023)
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 (2022)
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)
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 (2021)
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 (2021)
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) (2020)
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 (2020)
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 (2020)