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Adaptive Machine Unlearning
[article]
2021
arXiv
pre-print
Data deletion algorithms aim to remove the influence of deleted data points from trained models at a cheaper computational cost than fully retraining those models. However, for sequences of deletions, most prior work in the non-convex setting gives valid guarantees only for sequences that are chosen independently of the models that are published. If people choose to delete their data as a function of the published models (because they don't like what the models reveal about them, for example),
arXiv:2106.04378v1
fatcat:lgiq7qk2kvgonln3ktpafnlrx4