Modifications to a neural network's input and output layers are often required to accommodate the specificities of most practical learning tasks.

Privacy-protected microdata are often the desired output of a differentially private algorithm since microdata isfamiliar and convenient for downstream users. However, there is a statistical price for this kind of convenience.