Differentially Private SQL

Speaker: Professor Ke YI
         Department of Computer Science and Engineering
         HKUST

Title:   "Differentially Private SQL"

Date:    Monday, 28 March 2022

Time:    4:00pm - 5:00pm

Zoom link:
https://hkust.zoom.us/j/928308079?pwd=MW9wTCtlSDd2MnViZGdNd2oreUpXZz09

Meeting ID:     928 308 079
Passcode:       20212022

Abstract:

Privacy has become a major barrier for extracting valuable
information from data, due to either users' concerns or
regulatory requirements. As SQL remains the most widely used language for
querying and exploring data, the problem of how to answer SQL queries
under differential privacy has attracted a lot of attention in
recent years. However, most existing solutions are heuristics at best, due
to the fact that worst-case optimality is meaningless for most SQL queries
(except for the simplest cases), while instance optimality is too strong
to achieve. In this talk, I will introduce the framework of neighborhood
optimality, which is a natural relaxation of instance optimality, and
present some neighborhood optimal differentially private algorithms for
answering SQL queries.


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Biography:

Ke Yi is a Professor in the Department of Computer Science and
Engineering, Hong Kong University of Science and Technology. He obtained
his Bachelor's degree from Tsinghua University (2001) and PhD from Duke
University (2006), both in computer science. His research spans
theoretical computer science and database systems. His work has been
recognized by the 2016 SIGMOD Best Paper Award, a 2015 SIGMOD Best
Demonstration Award, a 2010 Google Faculty Research Award, and as a 2021
Distinguished Member of the ACM. He currently serves as an Associate
Editor for ACM Transactions on Database Systems.