Before revision:  It has been widely shown to improve accuracy. At the same time, ensemble learning has also been proposed to mitigate privacy leakage in terms of membership inference (MI), where the goal of an attacker is to infer whether a particular data sample has been used to train a target model .
After revision:  Ensemble learning has also been proposed to mitigate privacy leakage in terms of membership inference (MI), where the goal of an attacker is to infer whether a particular data sample has been used to train a target model .