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One-Shot Machine Unlearning with Mnemonic Code
A naive MU approach is to re-train the whole model with the training data from which the undesirable data has been removed.
Revisiting Permutation Symmetry for Merging Models between Different Datasets
We also show that merged models require datasets for merging in order to achieve a high accuracy.
ARDIR: Improving Robustness using Knowledge Distillation of Internal Representation
In addition to the output of the teacher model, ARDIR uses the internal representation of the teacher model as a label for adversarial training.
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