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October 12, 2016 @ 12:00 pm – 1:00 pm
Speaker: Justin Hsu
Affiliation: University of Pennsylvania
Title: Approximate Probabilistic Coupling and Differential Privacy
Abstract: Approximate lifting is a formal verification concept for proving
differential privacy. Recently, we have explored an interesting connection:
approximate liftings are an approximate version of probabilistic coupling. As a
consequence, we can give new, “coupling” proofs of differential privacy,
simplifying and generalizing existing proofs. In this talk we will present
approximate couplings and describe how to they can be used to prove differential
privacy for the Sparse Vector mechanism, an algorithm whose existing privacy
proof is notoriously subtle.
Joint with Gilles Barthe, Marco Gaboradi, Benjamin Gregoire, and Pierre-Yves Strub.