A dual data and loss-centric method claims to speed up machine unlearning, but its MIA regularizer cancels itself and the test set is leaked into training.
Boundary unlearning: Rapid forgetting of deep net- works via shifting the decision boundary
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Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster
A dual data and loss-centric method claims to speed up machine unlearning, but its MIA regularizer cancels itself and the test set is leaked into training.