  Iterative algorithms for differential privacy run for a fixed number of
iterations, where each iteration learns some information from data and produces
an intermediate output. However, the algorithm only releases the output of the
last iteration, and from which the accuracy of algorithm is judged. In this
paper, we propose a post-processing algorithm that seeks to improve the
accuracy by incorporating the knowledge on the data contained in intermediate
outputs.
