Poster: Secure Federated Learning Network Based on Client Selection

Contemporary applications leverage machine learning models to optimize performance, often necessitating data transmission to a remote server for training. However, this approach entails significant resource consumption. A privacy concern arises, ...

In a federated learning system, it is often the case that the more clients it involves, the less increment of the outcome it achieves. It is thus essential to design a client selection strategy to choose an appropriate subset of the clients to ...

Federated learning is a distributed machine learning approach that keeps data locally while achieving the utilization of fragmented data and protecting client privacy to a certain extent. However, the existence of data heterogeneity may cause ...