Privacy-Preserving Machine Learning: Towards More Efficient and Effective Methods
Research at TTIC Seminar Series
TTIC is hosting a weekly seminar series presenting the research currently underway at the Institute. Every week a different TTIC faculty member will present their research. The lectures are intended both for students seeking research topics and advisors, and for the general TTIC and University of Chicago communities interested in hearing what their colleagues are up to.
To attetnd via Zoom, register in advance here (this week, AV faults in the lecture room might impact streaming quality)
To receive announcements about the seminar series, please subscribe to the mailing list: https://groups.google.com/a/ttic.edu/group/talks/subscribe
Speaker details can be found at: http://www.ttic.edu/tticseminar.php.
For additional questions, please contact Nathan Srebro at email@example.com.
Host: Toyota Technological Institute at Chicago
Lingxiao Wang completed his Ph.D. in Computer Science from the University of California, Los Angeles in 2021. Previously he obtained his MS degree in Statistics at the University of Washington.
Lingxiao’s research interests are broadly in machine learning, including privacy-preserving machine learning, low-rank matrix learning, high-dimensional graphical models, and federated learning.