A privacy-preserving, distributed and cooperative FCM-based learning approach for Cancer Research

Autor:	Salmeron, Jose L., Arévalo, Irina
Rok vydání:	2024
Předmět:	Computer Science - Artificial Intelligence Computer Science - Distributed Parallel and Cluster Computing
Druh dokumentu:	Working Paper
Popis:	Distributed Artificial Intelligence is attracting interest day by day. In this paper, the authors introduce an innovative methodology for distributed learning of Particle Swarm Optimization-based Fuzzy Cognitive Maps in a privacy-preserving way. The authors design a training scheme for collaborative FCM learning that offers data privacy compliant with the current regulation. This method is applied to a cancer detection problem, proving that the performance of the model is improved by the Federated Learning process, and obtaining similar results to the ones that can be found in the literature. Comment: Rough Sets: International Joint Conference, IJCRS 2020
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2402.10102 Zobrazit plný text záznamu View this record from Arxiv