  We consider the problem of privately releasing a class of queries that we
call hierarchical count-of-counts histograms. Count-of-counts histograms
partition the rows of an input table into groups (e.g., group of people in the
same household), and for every integer j report the number of groups of size j.
Hierarchical count-of-counts queries report count-of-counts histograms at
different granularities as per hierarchy defined on an attribute in the input
data (e.g., geographical location of a household at the national, state and
county levels). In this paper, we introduce this problem, along with
appropriate error metrics and propose a differentially private solution that
generates count-of-counts histograms that are consistent across all levels of
the hierarchy.
