A Unified Approach to Differentially Private Bayes Point Estimation. (arXiv:2211.10332v1 [math.OC])

Parameter estimation in statistics and system identification relies on data
that may contain sensitive information. To protect this sensitive information,
the notion of \emph{differential privacy} (DP) has been proposed, which
enforces confidentiality by introducing randomization in the estimates.
Standard algorithms for differentially private estimation are based on adding
an appropriate amount of noise to the output of a traditional point estimation
method. This leads to an accuracy-privacy trade off, as adding more noise
reduces the accuracy while increasing privacy. In …

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