91 citations · 441 across the 36 of their papers we have counts for
43 papers
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…
Adaptive Data Analysis in a Balanced Adversarial Model
Kobbi Nissim, Uri Stemmer, Eliad Tsfadia
In adaptive data analysis, a mechanism gets i.i.d. samples from an unknown distribution , and is required to provide accurate estimations to a sequence of adaptively chosen…
On Differentially Private Online Predictions
Haim Kaplan, Yishay Mansour, Shay Moran +2
In this work we introduce an interactive variant of joint differential privacy towards handling online processes in which existing privacy definitions seem too restrictive. We stud…
Dynamic Algorithms Against an Adaptive Adversary: Generic Constructions and Lower Bounds
Amos Beimel, Haim Kaplan, Yishay Mansour +3
A dynamic algorithm against an adaptive adversary is required to be correct when the adversary chooses the next update after seeing the previous outputs of the algorithm. We obtain…
Computational Two-Party Correlation: A Dichotomy for Key-Agreement Protocols
Iftach Haitner, Kobbi Nissim, Eran Omri +2
Let be an efficient two-party protocol that given security parameter , both parties output single bits and , respectively. We are interested in how "a…
The Sample Complexity of Distribution-Free Parity Learning in the Robust Shuffle Model
Kobbi Nissim, Chao Yan
We provide a lowerbound on the sample complexity of distribution-free parity learning in the realizable case in the shuffle model of differential privacy. Namely, we show that the…