This publication contributes to work in data privacy, robust statistics, with a focus reflected in its title: Equivalence Testing Under Privacy Constraints.
This publication contributes to work in data privacy, applied statistics, with a focus reflected in its title: Large-Sample Bayesian Approximations for Privatized Data.
This publication contributes to work in data privacy, applied statistics, with a focus reflected in its title: Differentially Private Conformal Prediction via Quantile Binary Search.
This publication contributes to work in data privacy, applied statistics, with a focus reflected in its title: Fiducial Matching: Differentially Private Inference for Categorical Data.
This work highlights the links between statistical robustness and differential privacy, investigating a new method to protect data privacy using robust statistical tools
Given the increased push for data privacy, this project aims at delivering appropriate statistical tools for reliable inference in these settings.
An easy-to-read article highlighting the need and availability of solutions allowing the DoD to share more unclassified data with low disclosure risk