Hong kyu Lee

Contrastive Unlearning: A Contrastive Approach to Machine Unlearning

Machine unlearning aims to eliminate the influence of a subset of training samples (i.e., unlearning samples) from a trained model. Effectively and efficiently removing the unlearning samples without negatively impacting the overall model performance is challenging. Existing works mainly exploit inp