- Differential Privacy and Recommendation Systems
- Project Year:
2017
- REU Student (s):
Akilesh Tangella | University of Pennsylvania
- Student 1 Institution:
University of Pennsylvania
- Project Mentor:
Muthu Muthukrishnan
- Project Mentor Area:
Computer Science
- Project Abstract:
In this paper, we begin by introducing the concept of differential privacy and why it is a useful notion
of privacy compared to other approaches. We also introduce the locally distributed differential privacy
model. We then introduce various recommendation problems and formulate them mathematically. We
then introduce some theoretical tools useful in differential privacy and recommendation algorithms. We
then survey some existing literature in differential privacy to get the reader more familiar with how
it is applied in various settings and continue to survey various intersections of differential privacy and
recommendation algorithms. We end by identifying and precisely stating two open problems and discuss
approaches to solving them.
