A Theory to Instruct Differentially-Private Learning via Clipping Bias Reduction
Offered By: IEEE via YouTube
Course Description
Overview
Explore a 15-minute IEEE conference talk that delves into the theory of instructing differentially-private learning through clipping bias reduction. Learn about the research conducted by Hanshen Xiao from MIT, Zihang Xiang and Di Wang from KAUST, and Srinivas Devadas from MIT as they present their findings on this important topic in privacy-preserving machine learning.
Syllabus
A Theory to Instruct Differentially-Private Learning via Clipping Bias Reduction
Taught by
IEEE Symposium on Security and Privacy
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