Federated Learning Using Particle Swarm Optimization


Federated learning is a method that stores only learnt models on a server in order to protect data privacy. This approach does not collect data on the server but instead collects data from scattered clients directly. Due to the fact that federated learning clients frequently have limited transmission bandwidth, communication between servers and clients should be streamlined to maximize performance. As a result, researchers have created the FedPSO algorithm, which combines the particle swarm optimization technique with federated learning to boost network communication performance. We will attempt to cover certain aspects of this system and comprehend the proposed system in this post.