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cs.LG2022★ 7 cited
Verifiable and Provably Secure Machine Unlearning
Thorsten Eisenhofer, Doreen Riepel, Varun Chandrasekaran +3
Machine unlearning aims to remove points from the training dataset of a machine learning model after training: e.g., when a user requests their data to be deleted. While many unlea…
cs.LG2021
Property Inference From Poisoning
Melissa Chase, Esha Ghosh, Saeed Mahloujifar
Property inference attacks consider an adversary who has access to the trained model and tries to extract some global statistics of the training data. In this work, we study proper…