EAGER: Trustworthy and Verifiable Machine Unlearning in an Adversarial Environment

Overview

AI models are increasingly being trained on a huge amount of data. These models continuously need to remove selected data, or correct them to support a better accuracy or utility, and/or to comply with regulatory requirements such as the right to be forgotten/erasure/rectification. Machine Unlearning (MU) has emerged…