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When Machine Unlearning Jeopardizes Privacy
[article]
2020
arXiv
pre-print
The right to be forgotten states that a data owner has the right to erase her data from an entity storing it. In the context of machine learning (ML), the right to be forgotten requires an ML model owner to remove the data owner's data from the training set used to build the ML model, a process known as machine unlearning. While originally designed to protect the privacy of the data owner, we argue that machine unlearning may leave some imprint of the data in the ML model and thus create
arXiv:2005.02205v1
fatcat:nejb2afuqfe4pcrv463zgfjbna