machine unlearning

A technique that involves selectively removing the influences of spe­cific training data points from a trained machine learning model, such as to remove unwanted capabilities or knowledge in a foundation model, or to enable a user to request the removal of their records from a model. Efficient approximate unlearn­ing techniques may not require retraining the ML model from scratch.