PRIMO: Private Regression in Multiple Outcomes. (arXiv:2303.04195v1 [cs.LG])

We introduce a new differentially private regression setting we call Private
Regression in Multiple Outcomes (PRIMO), inspired the common situation where a
data analyst wants to perform a set of $l$ regressions while preserving
privacy, where the covariates $X$ are shared across all $l$ regressions, and
each regression $i \in [l]$ has a different vector of outcomes $y_i$. While
naively applying private linear regression techniques $l$ times leads to a
$\sqrt{l}$ multiplicative increase in error over the standard linear regression …

analyst call data data analyst outcomes privacy private techniques