“The winning paper is entitled Balancing Performance, Efficiency and Robustness in Open-World Machine Learning using Evolutionary Multi-objective Model Compression”.
TECNALIA wins prestigious IJCNN Best Paper Award at WCCI 2024
TECNALIA’s artificial intelligence research has reached a new level of excellence, after one of its papers presented at the IJCNN (International Joint Conference on Neural Networks) won the coveted IJCNN Best Paper Award.
The winning paper, entitled Balancing Performance, Efficiency and Robustness in Open-World Machine Learning using Evolutionary Multi-objective Model Compression, was presented by a research team led by Javier Del Ser, in collaboration with Aitor Martínez Seras, Nekane Bilbao, Jesús López Lobo, PhD, Ibai Laña, PhD and Francisco Herrera, at the World Congress on Computational Intelligence (WCCI 2024) held in Yokohama, Japan.
The WCCI 2024 brought together more than 2,000 attendees from around the world. It is the world’s largest intelligent computing in the world and brings together three sub-conferences: Fuzz-IEEE, CEC and the International Joint Conference on Neural Networks (IJCNN).
Artificial intelligence
This award is considered one of the most prestigious in the field of artificial intelligence. It is an international recognition of the outstanding research carried out by the TECNALIA team, in collaboration with the University of the Basque Country and the Andalusian Artificial Intelligence Institute (DaSCI).
The award-winning research focuses on developing more efficient and robust machine learning models: they use evolutionary computation techniques to optimise performance and efficiency in open learning environments.
