157 citations · 319 across the 33 of their papers we have counts for
5 papers · 1 filter
Measuring Re-identification Risk
CJ Carey, Travis Dick, Alessandro Epasto +8
Compact user representations (such as embeddings) form the backbone of personalization services. In this work, we present a new theoretical framework to measure re-identification r…
Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment
Rachel Cummings, Damien Desfontaines, David Evans +21
In this article, we present a detailed review of current practices and state-of-the-art methodologies in the field of differential privacy (DP), with a focus of advancing DP's depl…
Learning-Augmented Private Algorithms for Multiple Quantile Release
Mikhail Khodak, Kareem Amin, Travis Dick +1
When applying differential privacy to sensitive data, we can often improve performance using external information such as other sensitive data, public data, or human priors. We pro…
Smooth Anonymity for Sparse Graphs
Alessandro Epasto, Hossein Esfandiari, Vahab Mirrokni +1
When working with user data providing well-defined privacy guarantees is paramount. In this work, we aim to manipulate and share an entire sparse dataset with a third party private…
Plume: Differential Privacy at Scale
Kareem Amin, Jennifer Gillenwater, Matthew Joseph +2
Differential privacy has become the standard for private data analysis, and an extensive literature now offers differentially private solutions to a wide variety of problems. Howev…