Privacy-preserving data analysis is emerging as a challenging problem with far-reaching impact. In particular, synthetic are promising concept toward solving the aporetic conflict between privacy and sharing. Yet, it known that accurately generating private, of certain kinds NP-hard. We develop statistical framework for differentially private data, which enables us to circumvent computational h...