FedCIO: efficient exact federated unlearning with clustering, isolation, and one-shot aggregation

FedCIO: efficient exact federated unlearning with clustering, isolation, and one-shot aggregation

Data are invaluable in machine learning (ML), yet they raise significant privacy concerns. In the real world, data are often distributed across isolated silos, challenging conventional ML methods that centralize data. Federated learning (FL) offers a privacy-preserving solution that enables learning...

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Bibliographic Details
Main Authors: Qiu, Hongyu, Wang, Yongwei, Xu, Yonghui, Cui, Lizhen, Shen, Zhiqi
Other Authors: School of Computer Science and Engineering
Format: Conference Paper
Language:English
Published: 2024
Subjects:
Computer and Information Science
Federated learning
Machine unlearning
Online Access:https://hdl.handle.net/10356/173926

Internet

https://hdl.handle.net/10356/173926

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