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Differentially Private Sampling from Distributions
We demonstrate that, in some parameter regimes, private sampling requires asymptotically fewer observations than learning a description of $P$ nonprivately; in other regimes, however, private sampling proves to be as difficult as private learning.
Improved Differentially Private Analysis of Variance
Hypothesis testing is one of the most common types of data analysis and forms the backbone of scientific research in many disciplines.
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