most citedCertifying the Right to Be Forgotten: Primal-Dual Optimization for Sample and Label Unlearning in Vertical Federated Learning

6 citations · 6 across the 2 of their papers we have counts for

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cs.CR2026★ 6 cited

Certifying the Right to Be Forgotten: Primal-Dual Optimization for Sample and Label Unlearning in Vertical Federated Learning

Yu Jiang, Xindi Tong, Ziyao Liu +3

Federated unlearning has become an attractive approach to address privacy concerns in collaborative machine learning, for situations when sensitive data is remembered by AI models…

cs.CR2024

Efficient Federated Unlearning with Adaptive Differential Privacy Preservation

Yu Jiang, Xindi Tong, Ziyao Liu +3

Federated unlearning (FU) offers a promising solution to effectively address the need to erase the impact of specific clients' data on the global model in federated learning (FL),…