  We propose improving the privacy properties of a dataset by publishing only a
strategically chosen "core-set" of the data containing a subset of the
instances. The core-set allows strong performance on primary tasks, but forces
poor performance on unwanted tasks. We give methods for both linear models and
neural networks and demonstrate their efficacy on data.
