A distillation-based approach integrating continual learning and federated learning for pervasive services

Understand

Federated Learning, a new machine learning paradigm enhancing the use of edge devices, is receiving a lot of attention in the pervasive community to support the development of smart services.

• Nevertheless, this approach still needs to be adapted to the specificity of the pervasive domain.
• In particular, issues related to continual learning need to be addressed.
• In this paper, we present a distillation-based approach dealing with catastrophic forgetting in federated learning scenario.