Advances in Federated Learning: Applications and Challenges in Smart Building Environments and Beyond

Advances in Federated Learning: Applications and Challenges in Smart Building Environments and Beyond

Federated Learning (FL) is a transformative decentralized approach in machine learning and deep learning, offering enhanced privacy, scalability, and data security. This review paper explores the foundational concepts, and architectural variations of FL, prominent aggregation algorithms like FedAvg,...

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Bibliographic Details
Main Authors: Mohamed Rafik Aymene Berkani, Ammar Chouchane, Yassine Himeur, Abdelmalik Ouamane, Sami Miniaoui, Shadi Atalla, Wathiq Mansoor, Hussain Al-Ahmad
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Computers
Subjects:
federated Learning
deep learning
machine learning
Internet of Things
smart building
anomaly detection
Online Access:https://www.mdpi.com/2073-431X/14/4/124
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