Differential Privacy
@DiffPriv
Website for the differential privacy research community
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Open Problem: Selection via Low-Sensitivity Queries differentialprivacy.org/open-problem-s…
Happy new year! As promised, I wrote a blog post on the #NeurIPS2023 Outstanding Paper on privacy auditing, by @shortstein, @srxzr, Matthew Jagielski. Post is on @DiffPriv, 5 min read, written for a general ML audience. No knowlege of privacy needed! Link in next tweet👇
NeurIPS 2023 Outstanding Paper: Privacy auditing in just one run differentialprivacy.org/neurips23-op/
Open problem(s) - How generic can composition results be? differentialprivacy.org/open-problems-…
OpenDP is excited to bring you Library 0.8! Featuring improvements to OpenDP APIs, an early preview of functionality, and quality-of-life improvements. We'll discuss the new release at the OpenDP Community Meeting on September 29! github.com/opendp/opendp
Beyond Global Sensitivity via Inverse Sensitivity differentialprivacy.org/inverse-sensit…
Covariance-Aware Private Mean Estimation, Efficiently differentialprivacy.org/colt23-bsp/
#COLT2023 Mark Fulk award for best student paper is shared by two papers
The 2023 Caspar Bowden PET Award winner is: "The 2020 Census Disclosure Avoidance System TopDown Algorithm" #pets23
Call for Papers - TPDP 2023 - Submission deadline July 7 differentialprivacy.org/tpdp2023/
Open problem - Better privacy guarantees for larger groups differentialprivacy.org/open-problem-b…
Exciting! A book chapter on composition theorems in #differentialprivacy by @shortstein. Disclaimer: I'm a sucker for everything Thomas writes. arxiv.org/abs/2210.00597
I am looking to hire a PostDoc in differentially private synthetic data generation @MITIBMLab. If you are interested in differential privacy and generative modelling, please reach out via email. Recommendations and signal boosting appreciated!
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