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Federated Continual Learning through distillation in pervasive computing
Current solutions rely on the availability of large amounts of stored data at the client side in order to fine-tune the models sent by the server.
Federated Learning and catastrophic forgetting in pervasive computing: demonstration in HAR domain
Federated Learning has been introduced as a new machine learning paradigm enhancing the use of local devices.
A distillation-based approach integrating continual learning and federated learning for pervasive services
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.
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