VeriFi: Towards Verifiable Federated Unlearning

X Gao, X Ma, J Wang, Y Sun, B Li, S Ji… - … on Dependable and …, 2024 - ieeexplore.ieee.org
Federated learning (FL) has emerged as a privacy-aware collaborative learning paradigm
where participants jointly train a powerful model without sharing their private data. One …
被引用次数：40 相关文章

VeriFi: Towards Verifiable Federated Unlearning

X Gao, X Ma, J Wang, Y Sun, B Li, S Ji, P Cheng… - arXiv preprint arXiv …, 2022 - arxiv.org
Federated learning (FL) is a collaborative learning paradigm where participants jointly train
a powerful model without sharing their private data. One desirable property for FL is the …
[PDF] manchester.ac.uk

[PDF][PDF] VERIFI: Towards Verifiable Federated Unlearning

X Gao, X Ma, J Wang, Y Sun, B Li, S Ji, P Cheng… - pure.manchester.ac.uk
Federated learning (FL) has emerged as a privacyaware collaborative learning paradigm
where participants jointly train a powerful model without sharing their private data. One …

VeriFi: Towards Verifiable Federated Unlearning

X Gao, X Ma, J Wang, Y Sun, B Li, S Ji… - arXiv e …, 2022 - ui.adsabs.harvard.edu
Federated learning (FL) is a collaborative learning paradigm where participants jointly train
a powerful model without sharing their private data. One desirable property for FL is the …

VeriFi: Towards Verifiable Federated Unlearning

X Gao, X Ma, J Wang, Y Sun, B Li, S Ji… - IEEE Transactions on …, 2024 - computer.org
Federated learning (FL) has emerged as a privacy-aware collaborative learning paradigm
where participants jointly train a powerful model without sharing their private data. One …

VeriFi: Towards Verifiable Federated Unlearning

X Gao, X Ma, J Wang, Y Sun, B Li… - IEEE Transactions …, 2024 - research.manchester.ac.uk
Federated learning (FL) is a collaborative learning paradigm where participants jointly train
a powerful model without sharing their private data. One desirable property for FL is the …