A key challenge in many modern data analysis tasks is that user data are...
We revisit the problem of designing scalable protocols for private stati...
In this work, we study practical heuristics to improve the performance o...
Privately learning statistics of events on devices can enable improved u...
The shuffle model of differential privacy has gained significant interes...
Differential privacy is a restriction on data processing algorithms that...
Recent work of Erlingsson, Feldman, Mironov, Raghunathan, Talwar, and
Th...
Social science and economics research is often based on data collected i...
Economics and social science research often require analyzing datasets o...
In this work we present novel differentially private identity
(goodness-...
Hypothesis testing plays a central role in statistical inference, and is...
We consider the problem of property testing for differential privacy: wi...
In this work we explore the utility of locally differentially private th...