PhD Proposal: Scalable Methods for Robust Machine Learning
Alexander Levine
Abstract
|
|
Bio
Alex Levine is a fourth year PhD student at the University of Maryland, advised by Dr. Soheil Feizi. His work focuses primarily on adversarial robustness in machine learning. He received his MS from UMD in 2020, and his bachelor's degree from Brown University in 2016.
This talk is organized by Tom Hurst