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Differential privacy (DP) is a framework to quantify to what extent individual privacy in a statistical database is preserved while releasing useful aggregate information about the database. In this work, we aim an exploratory study to understand questions related to the optimality of noise generation mechanisms (NGMs) in differential privacy by taking into consideration the (i) query sensitivity,...
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