1. Collective self-learning by exchanging ML models
- Author
-
Patricia Layec, Marc Ruiz Ramírez, Fabien Boitier, Luis Domingo Velasco Esteban, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, and Universitat Politècnica de Catalunya. GCO - Grup de Comunicacions Òptiques
- Subjects
Informàtica::Intel·ligència artificial::Aprenentatge automàtic [Àrees temàtiques de la UPC] ,Autonomic transmission ,02 engineering and technology ,language.human_language ,020210 optoelectronics & photonics ,Pedagogy ,Institution (computer science) ,Machine learning ,Aprenentatge automàtic ,0202 electrical engineering, electronic engineering, information engineering ,language ,Catalan ,Sociology ,Collective self ,Self-learning - Abstract
Collective self-learning based on Machine Learning (ML) model sharing and combination is proposed to accelerate ML-based algorithm deployment. The considered architecture is presented, together with different alternatives for combining ML models. Performance analysis is carried out on an illustrative use case for autonomic optical transmission. The research leading to these results has received funding from the AEI/FEDER TWINS project (TEC2017-90097-R), from the EC METRO-HAUL project (G.A. nº 761727), and from the Catalan ICREA Institution.
- Published
- 2019