Differential privacy disentangles learning about a dataset as a whole from learning about an individual data contributor. Just now entering practice on a global scale, the demand for advanced differential privacy techniques and knowledge of basic skills is pressing. This symposium will provide an in-depth look at the current context for privacy-preserving statistical data analysis and an agenda for future research. This event is organized by Cynthia Dwork, of Microsoft Research, with support from the Alfred P. Sloan Foundation.
Helen Nissenbaum, Cornell Tech and NYU
Aaron Roth, University of Pennsylvania
Guy Rothblum, Weizmann Institute
Kunal Talwar, Google Brain
Jonathan Ullman, Northeastern University