Machine learning models are famously vulnerable to adversarial attacks: small ad-hoc perturbations of the data that can catastrophically alter the model predictions.

Foreffectiveknowledge transfer,weadopt the idea of domain classifier so that student training is guided by discriminative features invariant totherepresentational space shift between teacher andstudent.