From the 1 of 4 linked papers with an AI index.
4 papers
Pure-DP Statistical Query Release at the Conjectured Square-Root Rate
Jack Fitzsimons
Nikolov and Ullman asked whether k statistical queries on a universe of size T can be released under pure differential privacy with expected worst-coordinate error at the square-ro…
Better Privacy Guarantees for Larger Groups
Jack Fitzsimons, JacK Fitzsimons
The paper investigates private histograms under a count‑dependent zero‑concentrated differential privacy model, proving that an inverse‑square privacy budget dependence on group si…
Privacy in Theory, Bugs in Practice: Grey-Box Auditing of Differential Privacy Libraries
Tudor Cebere, David Erb, Damien Desfontaines +2
Differential privacy (DP) implementations are notoriously prone to errors, with subtle bugs frequently invalidating theoretical guarantees. Existing verification methods are often…
Private Means and the Curious Incident of the Free Lunch
Jack Fitzsimons, James Honaker, Michael Shoemate +1
We show that the most well-known and fundamental building blocks of DP implementations -- sum, mean, count (and many other linear queries) -- can be released with substantially red…