unsupervised continual learning (UCL) is a burgeoning field in machine
learning, focusing on enabling neural networks to sequentially learn tasks
without explicit label information. catastrophic forgetting (CF),
Federated Continual Learning (FCL) integrates federated learning and continual learning to address the challenge of data privacy and silos, by fusing heterogeneous knowledge from different clients and retaining knowledge of previous tasks while learning on new ones, through methods such as synchronous FCL and asynchronous FCL.