73 citations · 585 across the 58 of their papers we have counts for
4 papers · 1 filter
Instance-Optimal Differentially Private Estimation
Audra McMillan, Adam Smith, Jon Ullman
In this work, we study local minimax convergence estimation rates subject to -differential privacy. Unlike worst-case rates, which may be conservative, algorithms that are local…
Multitask Learning via Shared Features: Algorithms and Hardness
Konstantina Bairaktari, Guy Blanc, Li-Yang Tan +2
We investigate the computational efficiency of multitask learning of Boolean functions over the -dimensional hypercube, that are related by means of a feature representation of…
SNAP: Efficient Extraction of Private Properties with Poisoning
Harsh Chaudhari, John Abascal, Alina Oprea +3
Property inference attacks allow an adversary to extract global properties of the training dataset from a machine learning model. Such attacks have privacy implications for data ow…
How to Combine Membership-Inference Attacks on Multiple Updated Models
Matthew Jagielski, Stanley Wu, Alina Oprea +2
A large body of research has shown that machine learning models are vulnerable to membership inference (MI) attacks that violate the privacy of the participants in the training dat…