BriefGPT.xyz
Sep, 2024
统一的基于梯度的机器遗忘与剩余几何增强
Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement
HTML
PDF
Zhehao Huang, Xinwen Cheng, JingHao Zheng, Haoran Wang, Zhengbao He...
TL;DR
该研究解决了现有机器遗忘方法在大规模模型中效率低下的问题,提出了一种通过嵌入剩余几何的方式来优化遗忘更新的新方法。研究结果表明,该方法能够在不影响保留性能的情况下,显著提升遗忘效率,在ImageNet和CIFAR-10等数据集上验证了其有效性。
Abstract
Machine Unlearning
(MU) has emerged to enhance the privacy and trustworthiness of
Deep Neural Networks
. Approximate MU is a practical method for large-scale models. Our investigation into approximate MU starts wi
→