Next, we train a linear classifier as per , Equation 3 on the datasets D ^ det \hat{\mathcal{D}}_{\text{det}} D ^ det ​ and D ^ rand \hat{\mathcal{D}}_{\text{rand}} D ^ rand ​ (Defined , Table 1) on these robust features only. We find features that satisfy both specifications by using the 10 linear features of a robust linear model trained on CIFAR-10. Training a linear model on the above robust features on D ^ rand \hat{\mathcal{D}}_{\text{rand}} D^rand​ and testing on the CIFAR test set incurs an accuracy of 23.5% (out of 88%).