Differential privacy has been widely adopted to release continuous- and scalar-valued information on a database without compromising the of individual data records in it. The problem querying binary- matrix-valued differentially private manner rarely studied. However, are ubiquitous real-world applications, whose concerns may arise under variety circumstances. In this paper, we devise an exclus...

In this paper we study methods for estimating causal effects in settings with panel data, where some units are exposed to a treatment during periods and the goal is counterfactual (untreated) outcomes treated unit/period combinations. We propose class of matrix completion estimators that uses observed elements control corresponding untreated unit/periods impute "missing" outcome matrix, units/p...