Learnability and Privacy Vulnerability are Entangled in a Few Critical Weights

ArXi:2603.13186v1 Announce Type: cross Prior approaches for membership privacy preservation usually update or retrain all weights in neural networks, which is costly and can lead to unnecessary utility loss or even serious misalignment in predictions between