collaborators

5 papers

cs.CR2026

Optimal partition selection with Rényi differential privacy

Charlie Harrison, Pasin Manurangsi

A common problem in private data analysis is the partition selection problem, where each user holds a set of partitions (e.g. keys in a GROUP BY operation) from a possibly unbounde…

cs.CR2025

Exact zCDP Characterizations for Fundamental Differentially Private Mechanisms

Charlie Harrison, Pasin Manurangsi

Zero-concentrated differential privacy (zCDP) is a variant of differential privacy (DP) that is widely used partly thanks to its nice composition property. While a tight conversion…

cs.CR2025

Infinitely Divisible Noise for Differential Privacy: Nearly Optimal Error in the High Regime

Charlie Harrison, Pasin Manurangsi

Differential privacy (DP) can be achieved in a distributed manner, where multiple parties add independent noise such that their sum protects the overall dataset with DP. A common t…

cs.CR2025

On the Differential Privacy and Interactivity of Privacy Sandbox Reports

Badih Ghazi, Charlie Harrison, Arpana Hosabettu +8

The Privacy Sandbox initiative from Google includes APIs for enabling privacy-preserving advertising functionalities as part of the effort around limiting third-party cookies. In p…

cs.LG2025

Balls-and-Bins Sampling for DP-SGD

Lynn Chua, Badih Ghazi, Charlie Harrison +6

We introduce the Balls-and-Bins sampling for differentially private (DP) optimization methods such as DP-SGD. While it has been common practice to use some form of shuffling in DP-…