Distributed training of Deep Learning (DL) models on resource-constrained devices has
gained significant interest. Training data-driven DL models collaboratively using federated …

Federated learning (FL) is a distributed machine learning framework where multiple clients
collaboratively train a model without sharing their data. Despite advancements, traditional …

Fully decentralized learning algorithms are still in an early stage of development. Creating
modular Gossip Learning strategies is not trivial due to convergence challenges and …

The advent of the Internet of Things (IoT) led to the significance of fully decentralized
(serverless) learning that enables individual models to preserve specific values such as …