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cs.CR2022
Federated Learning for Tabular Data: Exploring Potential Risk to Privacy
Han Wu, Zilong Zhao, Lydia Y. Chen +1
Federated Learning (FL) has emerged as a potentially powerful privacy-preserving machine learning methodology, since it avoids exchanging data between participants, but instead exc…
cs.CR2022★ 1 cited
Fabricated Flips: Poisoning Federated Learning without Data
Jiyue Huang, Zilong Zhao, Lydia Y. Chen +1
Attacks on Federated Learning (FL) can severely reduce the quality of the generated models and limit the usefulness of this emerging learning paradigm that enables on-premise decen…