Asynchronous Federated Unlearning

Ningxin Su, Baochun Li, University of Toronto, IEEE International Conference on Computer Communications (INFOCOM) 2023 [Paper] [Slides] [Source Code] Thanks to regulatory policies such as the General Data Protection Regulation (GDPR), it is essential to provide users with the right to erasure regarding their own private data, even if such data has been used to train a neural network model.
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How Asynchronous can Federated Learning Be?

Ningxin Su, Baochun Li, University of Toronto, IEEE International Symposium on Quality of Service (IWQoS) 2022 [Paper] [Slides] [Source Code] As a practical paradigm designed to involve large numbers of edge devices in distributed training of deep learning models, federated learning has witnessed a significant amount of research attention in the recent years.
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