New technologies bring opportunities to deploy AI and machine learning to the edge of the
network, allowing edge devices to train simple models that can then be deployed in practice …

Recent progress in machine learning frameworks has made it possible to now perform
inference with models using cheap, tiny microcontrollers. Training of machine learning …

Federated learning (FL) is a decentralized machine learning (ML) technique that learns from
distributed data by moving the training process from a centralized server towards many …

Smart city applications that request sensitive user information necessitate a comprehensive
data privacy solution. Federated learning (FL), also known as privacy by design, is a new …

This study focuses on optimizing federated learning in heterogeneous data environments.
We implement the FedProx and a baseline algorithm (ie, the FedAvg) with advanced …

Featured Application The proposed protocol can be applied to systems utilizing federated
learning. The design takes into account systems that necessitate both redundant and secure …

Healthcare systems around the world rely on powerful computational prediction tools in
order to make accurate diagnostics with regard to the human body. In order to estimate the …