Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

Abstract: Federated learning is an important distributed machine learning paradigm. This study proposes a privacy-preserving data augmentation model for federated learning of heterogeneous data, which ...

Abstract: As a new paradigm that integrates clustering with federated learning, federated clustering (FC) has recently attracted increasing attention, as it addresses the practical issue of privacy ...