Safe ML: robustness, verification and Privacy
Shafi Goldwasser (UC Berkeley)
Distinguished Lecture Series
Thursday, February 17, 2022, 3:30 pm
Virtual
Abstract
We will present cryptography inspired models of adversaries in the machine learning landscape and results to address three challenges. These challenges include verification of machine learning models given limited access to good data, training at scale on private training data, and robustness against adversarial examples controlled by worst-case adversaries
Bio
Shafi Goldwasser is the Director of the Simons Institute for the Theory of Computing, and the C. Lester Hogan Professor in Electrical Engineering and Computer Sciences at UC Berkeley. She is also the RSA Professor of Electrical Engineering and Computer Science at MIT, a professor of computer science and applied mathematics at the Weizmann Institute of Science in Israel and a co-founder of Duality Technologies. Goldwasser received a BS in applied mathematics from Carnegie Mellon University in 1979, and MS and PhD in computer science from UC Berkeley in 1984.
Goldwasser is a co-inventor of interactive proofs and zero knowledge proofs and has received a number of awards for her contributions to cryptography and computer science, including the ACM Turing Award (2012). She is a member of the AAAS, ACM, NAE, NAS, Israeli Academy of Science, London Mathematical Society, and Russian Academy of Science.