Releasing Malevolence from Benevolence: The Menace of Benign Data on
Machine Unlearning
Releasing Malevolence from Benevolence: The Menace of Benign Data on
Machine Unlearning
Machine learning models trained on vast amounts of real or synthetic data often achieve outstanding predictive performance across various domains. However, this utility comes with increasing concerns about privacy, as the training data may include sensitive information. To address these concerns, machine unlearning has been proposed to erase specific data …