2025
When Data Can't Meet: Estimating Correlation Across Privacy Barriers
NeurIPS 2025spotlight
We consider the problem of estimating the correlation of two random variables $X$ and $Y$, where the pairs $(X,Y)$ are not observed together, but are instead separated co-ordinate-wise at two servers: server 1 contains all the $X$ observations, and server 2 contains the corresponding $Y$ observation…