Refreshments are available starting at 10:30 a.m. The seminar will begin at 10:45 a.m.
Abstract
Data-driven systems hold immense potential to positively impact society, but their reliability remains a challenge. Their outputs are often too brittle to changes in their training data, leaving them vulnerable to data poisoning attacks, prone to leaking sensitive information, or susceptible to overfitting. Establishing fundamental principles for designing algorithms that are both stable—to mitigate these risks—and efficient in their use of resources is essential for enabling trustworthy data-driven systems.
In this talk, Lydia Zakynthinou will focus on statistical estimation under differential privacy—a rigorous framework that ensures data-driven system outputs do not reveal sensitive information about individuals in their input. She will present algorithmic techniques that take advantage of beneficial structure in the data to achieve optimal error for several multivariate tasks without requiring any prior information about the data by building on robustness against data poisoning attacks. Lastly, Zakynthinou will highlight the deeper connection between differential privacy and robustness that underpins these results.
Speaker Biography
Lydia Zakynthinou is a Foundations of Data Science Institute postdoctoral research fellow in the Simons Institute for the Theory of Computing at the University of California, Berkeley, hosted by Michael I. Jordan. Zakynthinou earned her PhD in computer science from Northeastern University under the supervision of Jonathan Ullman and Huy Nguyen. Her research lies in trustworthy machine learning and statistics, with a focus on data privacy and generalization, and has been recognized with a Meta Research PhD Fellowship and a Khoury College PhD Research Award. Zakynthinou holds a diploma in electrical and computer engineering from the National Technical University of Athens and an MSc in logic, algorithms, and theory of computation from the National and Kapodistrian University of Athens in Greece.