Introducing a Quality-Driven Approach for Federated Learning

Introducing a Quality-Driven Approach for Federated Learning

The advancement of pervasive systems has made distributed real-world data across multiple devices increasingly valuable for training machine learning models. Traditional centralized learning approaches face limitations such as data security concerns and computational constraints. Federated learning...

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Bibliographic Details
Main Authors: Muhammad Usman, Mario Luca Bernardi, Marta Cimitile
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Sensors
Subjects:
federated learning
machine learning
data fusion
data imbalance
neural network
Online Access:https://www.mdpi.com/1424-8220/25/10/3083
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