Aritz D. Martinez

According to our database, Aritz D. Martinez authored at least 15 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

EvoPruneDeepTL: An evolutionary pruning model for transfer learning based deep neural networks.

Javier Poyatos, Daniel Molina, Aritz D. Martinez, Javier Del Ser, Francisco Herrera

Neural Networks, January, 2023

2022

Adaptive Multifactorial Evolutionary Optimization for Multitask Reinforcement Learning.

Aritz D. Martinez, Javier Del Ser, Eneko Osaba, Francisco Herrera

IEEE Trans. Evol. Comput., 2022

Evolutionary Multitask Optimization: a Methodological Overview, Challenges, and Future Research Directions.

Eneko Osaba, Javier Del Ser, Aritz D. Martinez, Amir Hussain

Cogn. Comput., 2022

A Multifactorial Cellular Genetic Algorithm for Multimodal Multitask Optimization.

Eneko Osaba, Javier Del Ser, Aritz D. Martinez, Jesus L. Lobo

Proceedings of the IEEE Congress on Evolutionary Computation, 2022

2021

AT-MFCGA: An Adaptive Transfer-guided Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking.

Eneko Osaba, Javier Del Ser, Aritz D. Martinez, Jesus L. Lobo, Francisco Herrera

Inf. Sci., 2021

Lights and shadows in Evolutionary Deep Learning: Taxonomy, critical methodological analysis, cases of study, learned lessons, recommendations and challenges.

Aritz D. Martinez, Javier Del Ser, Esther Villar-Rodriguez, Eneko Osaba, Javier Poyatos, Siham Tabik, Daniel Molina, Francisco Herrera

Inf. Fusion, 2021

Evolutionary Multitask Optimization: a Methodological Overview, Challenges and Future Research Directions.

Eneko Osaba, Aritz D. Martinez, Javier Del Ser

CoRR, 2021

More is not Always Better: Insights from a Massive Comparison of Meta-heuristic Algorithms over Real-Parameter Optimization Problems.

Javier Del Ser, Eneko Osaba, Aritz D. Martinez, Miren Nekane Bilbao, Javier Poyatos, Daniel Molina, Francisco Herrera

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

MO-MFCGA: Multiobjective Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking.

Eneko Osaba, Javier Del Ser, Aritz D. Martinez, Jesus L. Lobo, Antonio J. Nebro, Xin-She Yang

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Collaborative Exploration and Reinforcement Learning between Heterogeneously Skilled Agents in Environments with Sparse Rewards.

Alain Andres, Esther Villar-Rodriguez, Aritz D. Martinez, Javier Del Ser

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

On the Transferability of Knowledge among Vehicle Routing Problems by using Cellular Evolutionary Multitasking.

Eneko Osaba, Aritz D. Martinez, Jesus L. Lobo, Ibai Laña, Javier Del Ser

Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

dMFEA-II: An adaptive multifactorial evolutionary algorithm for permutation-based discrete optimization problems.

Eneko Osaba, Aritz D. Martinez, Akemi Gálvez, Andrés Iglesias, Javier Del Ser

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Multifactorial Cellular Genetic Algorithm (MFCGA): Algorithmic Design, Performance Comparison and Genetic Transferability Analysis.

Eneko Osaba, Aritz D. Martinez, Jesus L. Lobo, Javier Del Ser, Francisco Herrera

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

Simultaneously Evolving Deep Reinforcement Learning Models using Multifactorial optimization.

Aritz D. Martinez, Eneko Osaba, Javier Del Ser, Francisco Herrera

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019

Hybridizing differential evolution and novelty search for multimodal optimization problems.

Aritz D. Martinez, Eneko Osaba, Izaskun Oregi, Iztok Fister Jr., Iztok Fister, Javier Del Ser

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019