Shows
International Conference on Functional Programming 2017A Framework for Adaptive Differential PrivacyDaniel Winograd-Cort University of Pennsylvania, USA, gives the first presentation in the third panel, Applications, in the ICFP 2017 conference. Co-written by Andreas Haeberlen and Aaron Roth, University of Pennsylvania, USA. Differential privacy is a widely studied theory for analyzing sensitive data with a strong privacy guarantee--any change in an individual's data can have only a small statistical effect on the result--and a growing number of programming languages now support differentially private data analysis. A common shortcoming of these languages is poor support for adaptivity. In practice, a data analyst rarely wants to run just one function over a sensitive database...2017-12-1318 min