Abstract: Metaheuristics are widely recognized gradient-free solvers to hard problems that do not meet the rigorous mathematical assumptions of conventional solvers. The automated design of ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results