We construct differentially private estimators with low sample complexit...
Recent work of Acharya et al. (NeurIPS 2019) showed how to estimate the
...
We investigate the local differential privacy (LDP) guarantees of a
rand...
Understanding the shape of a distribution of data is of interest to peop...
Aggregating data is fundamental to data analytics, data exploration, and...
Determinantal point processes (DPPs) are popular probabilistic models of...
We propose a new setting for testing properties of distributions while
r...
There has been significant study on the sample complexity of testing
pro...
In this work, we consider the sample complexity required for testing the...
We investigate the problems of identity and closeness testing over a dis...