The success of machine learning (ML) techniques in the formerly difficult areas of data
analysis and pattern extraction has led to their widespread incorporation into various …

Abstract The Fourth Industrial Revolution suggests smart and automated industrial solutions
by incorporating Artificial Intelligence into it. Today, the world of technology is highly …

Federated learning (pioneered by Google) is a new class of machine learning models
trained on distributed data sets, and equally important, a key privacy-preserving data …

This paper provides a comprehensive study of Federated Learning (FL) with an emphasis
on enabling software and hardware platforms, protocols, real-life applications and use …

With the growing concern on data privacy and security, it is undesirable to collect data from
all users to perform machine learning tasks. Federated learning, a decentralized learning …

Federated learning (FL) is a collaborative, decentralized privacy‐preserving method to
attach the challenges of storing data and data privacy. Artificial intelligence, machine …

Federated Learning (FL) is an approach to machine learning in which the training data are
not managed centrally. Data are retained by data parties that participate in the FL process …

Federated learning (FL) is a machine learning setting where many clients (eg, mobile
devices or whole organizations) collaboratively train a model under the orchestration of a …

Federated Learning (FL) is a distributed machine learning approach in which clients
contribute to learning a global model in a privacy preserved manner. Effective aggregation …

Federated learning is a promising approach for collaboratively training machine learning
models while keeping the training data decentralized. This paper discusses recent …