… Federated learning (FL) is an emerging tool involving a decentralized machine learning (ML) …
Furthermore, in the context of global competition, the need for organizations to remain …

… the US, highlighting both the challenges and opportunities for federated learning in the context
of … By leveraging federated learning, organizations can harness the power of collaborative …

… federated learning setup, an adversary has many more opportunities to poison one of the local
machine learning … Organizations and industries are faced with a growing number of cyber-…

… In addition to this, federated learning makes it possible for organizations with limited
resources to take part in collaborative model training and reap the benefits of pooled knowledge. …

… Even departments within the same organization can face resistance against data integration
… Federated learning (FL) is capable of simultaneously addressing critical bottlenecks of data …

… to learn effective strategies for organizations interacting in … Specifically, AIFL aims to learn
an organization’s data contri… design for federated learning: Challenges and opportunities,…

… variants of federated learning through the federated learning framework. In this section
we will explain federated learning and present the framework of federated learning used to …

… study introduces a privacy-preserving federated learning method, which combines airline …
through federated learning. The result shows that the joint model based on federated learning …

… To attenuate this, a centralized learning strategy cannot be used in cases where there is
a risk of data privacy breach, particularly in healthcare centers. Federated learning (FL) is a …

… such federated learning frameworks to combat COVID-19. … on federated learning theories
and their applications in 5G and beyond communication networks. The federated learning …