Machine Unlearning by Suppressing Sample Contribution

arXiv:2402.15109v1 Announce Type: new
Abstract: Machine Unlearning (MU) is to forget data from a well-trained model, which is practically important due to the "right to be forgotten". In this paper, we start from the fundamental distinction between training data and unseen data on their contribution to the model: the training data contributes to the final model while the unseen data does not. We theoretically discover that the input sensitivity can approximately measure the contribution and practically design an algorithm, called …

abstract arxiv cs.lg data machine paper sample training training data type unlearning