May 14, 2024, 4:11 a.m. | Weiqi Wang, Zhiyi Tian, Shui Yu

cs.CR updates on

arXiv:2405.07406v1 Announce Type: new
Abstract: As the right to be forgotten has been legislated worldwide, many studies attempt to design unlearning mechanisms to protect users' privacy when they want to leave machine learning service platforms. Specifically, machine unlearning is to make a trained model to remove the contribution of an erased subset of the training dataset. This survey aims to systematically classify a wide range of machine unlearning and discuss their differences, connections and open problems. We categorize current unlearning …

arxiv design machine machine learning platforms privacy protect remove right to be forgotten service studies survey training

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