Vincent Quirion

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data

Noise-based certified machine unlearning currently faces a hard ceiling: the noise magnitude required to certify unlearning typically destroys model utility, particularly for large-scale deletion requests. While leveraging public data is a standard technique in differential privacy to relax this ten…