3 papers
cs.LG2023
Private Everlasting Prediction
Moni Naor, Kobbi Nissim, Uri Stemmer +1
A private learner is trained on a sample of labeled points and generates a hypothesis that can be used for predicting the labels of newly sampled points while protecting the privac…
cs.CR2022
Necessary Conditions in Multi-Server Differential Privacy
Albert Cheu, Chao Yan
We consider protocols where users communicate with multiple servers to perform a computation on the users' data. An adversary exerts semi-honest control over many of the parties bu…
cs.CR2021
Pure Differential Privacy from Secure Intermediaries
Albert Cheu, Chao Yan
Recent work in differential privacy has explored the prospect of combining local randomization with a secure intermediary. Specifically, there are a variety of protocols in the sec…