Less Noise, Same Certificate: Retain Sensitivity for Unlearning
The paper introduces Retain Sensitivity (RS) as a way to calibrate noise for certified unlearning, aiming to reduce noise requirements compared to global sensitivity analysis. Calibrating noise based on RS is sufficient to guarantee (ε, δ)-unlearning across various machine learning problems like MST and PCA, leading to significant performance gains in active unlearning algorithms.