We have seen that additive noise technique is not (SV (γ), ε)-DP. So, the question that we explore in todays class is whether differential privacy (DP) is achievable with SV sources. Interestingly, we give a differential private mechanism for approximate arbitrary “low sensitive” functions that works even with randomness coming from SV source, for any γ < 1. We conclude todays lecture with some...