A Federated Learning-Inspired Evolutionary Algorithm: Application to Glucose Prediction

In this paper, we propose an innovative Federated Learning-inspired evolutionary framework. Its main novelty is that this is the first time that an Evolutionary Algorithm is employed on its own to directly perform Federated Learning activity. A further novelty resides in the fact that, differently f...

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Vydané v:	Sensors (Basel, Switzerland) Ročník 23; číslo 6; s. 2957
Hlavní autori:	De Falco, Ivanoe, Della Cioppa, Antonio, Koutny, Tomas, Ubl, Martin, Krcma, Michal, Scafuri, Umberto, Tarantino, Ernesto
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 01.03.2023 MDPI
Predmet:	Algorithms Artificial intelligence Data security Dextrose Diabetes Diabetics evolutionary algorithms Explicit knowledge federated learning Forecasts and trends General Data Protection Regulation Genetic algorithms Glucose Humans interpretable machine learning Knowledge Learning Machine Learning Privacy Florida United States Ohio diabetes interpretable machine learning evolutionary algorithms federated learning
ISSN:	1424-8220, 1424-8220
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