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Hessian-guided gradient unlearning

delete2026-09-16
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OA
AI
A
Abdullah Ahmad Khan
M
Mohammed Kaosar
H
Hamid Laga
F
Ferdous Sohel *
DOI：10.1016/j.neucom.2026.135115delete
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摘要

摘要

En 中文
• 提出了一种基于Hessian引导的梯度遗忘（HGU）框架，用于深度模型中的可扩展数据移除。 • 结合梯度效率和基于Hessian的精确性，以提升遗忘性能。 • 引入了曲率感知更新，能够在不进行完整模型再训练的情况下近似再训练过程。 • 实现了89.8%的保留准确率和48.4%的遗忘类别准确率。 • 验证了在CIFAR-10、ImageNet-Subset和网级数据集上的可扩展性。
Keyword:
Machine unlearning
Gradient-based unlearning
Hessian-based approximation
Inpainting
Data privacy
Responsible AI
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Neurocomputing 封面图
Neurocomputing
IF:
6.5
论文数:
2.5W
被引数:
6.5W

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