| According to a method provided in the disclosure, based on an original signal and an information elimination (IE) model, a feature not including information allowing an attribute to be recognizable is generated. A task is then performed using a machine learning model based on the generated feature. For training the IE model, two adversarial networks are provided and a loss function is minimized. Input layers of the two adversarial networks are generated based on output layer and input features of the IE model. Generator of one adversarial network and discriminator of the other adversarial network are configured to perform the task, while discriminator of the one adversarial network and generator of the other adversarial network are configured to recognize the attribute. The loss function is associated with a disentangling loss of input layers of the two adversarial networks, as well as losses of each generator and discriminator. |