With the continuous development of Artificial Intelligence (AI), AI services are becoming
increasingly influential in society, affecting both individual lives and enterprise production …

Federated learning has emerged as a promising paradigm in the domain of distributed
artificial intelligence (AI) systems, enabling collaborative model training across …

Federated learning (FL) is a distributed machine learning approach that can achieve the
purpose of collaborative learning from a large amount of data that belong to different parties …

The 5.0 era's arrival and the ongoing advancement of technology have had a significant
impact on many facets of our society, including education. There is increased interest in …

Federated learning (FL) is an emerging technology that enables the training of machine
learning models from multiple clients while keeping the data distributed and private. Based …

Federated learning (FL) has emerged as one of the de-facto privacy-preserving paradigms
that can effectively work with decentralized data sources (eg, hospitals) without acquiring …

Federated Learning (FL) proposed in recent years has received significant attention from
researchers in that it can enable multiple clients to cooperatively train global models without …

Federated learning (FL) is a distributed machine learning strategy that generates a global
model by learning from multiple decentralized edge clients. FL enables on-device training …

Federated learning (FL) is an emerging setting which implement machine learning in a
distributed environment while protecting privacy. Research activities relating to FLhave …

Federated learning (FL) enables multiple data owners to build machine learning models
collaboratively without exposing their private local data. In order for FL to achieve …