A Theory to Instruct Differentially-Private Learning via Clipping Bias Reduction
Security researchers examine technical aspects of A Theory to Instruct Differentially-Private Learning via Clipping Bias Reduction.
Summary
No summary yet — watch the video above, or open it on YouTube.
Related talks
IEEE Symposium on Security and Privacy·21 min
Engineers explore architecture and security mechanisms for Learning to Reconstruct: Statistical Learning Theory and Encrypted Database Attacks.
databaselearningreconstruct+3
IEEE Symposium on Security and Privacy·12 min
Extreme Multi-label Learning
Presenters detail vulnerability discovery and exploitation in XFL: Naming Functions in Binaries with Extreme Multi-label Learning.
namingfunctionbinarie+3
IEEE Symposium on Security and Privacy·14 min
Security researchers examine technical aspects of LAMBRETTA: Learning to Rank for Twitter Soft Moderation.
twitterlambrettalearning+3


