Partially Blinded Unlearning: Class Unlearning for Deep Networks a Bayesian Perspective

arXiv:2403.16246v1 Announce Type: new
Abstract: In order to adhere to regulatory standards governing individual data privacy and safety, machine learning models must systematically eliminate information derived from specific subsets of a user's training data that can no longer be utilized. The emerging discipline of Machine Unlearning has arisen as a pivotal area of research, facilitating the process of selectively discarding information designated to specific sets or classes of data from a pre-trained model, thereby eliminating the necessity for extensive retraining …

abstract arxiv bayesian class cs.cv cs.lg data data privacy information machine machine learning machine learning models networks perspective privacy regulatory safety standards subsets training training data type unlearning