11 citations · 11 across the 2 of their papers we have counts for
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cs.CR2021
Differentially Private Histograms in the Shuffle Model from Fake Users
Albert Cheu, Maxim Zhilyaev
There has been much recent work in the shuffle model of differential privacy, particularly for approximate -bin histograms. While these protocols achieve low error, the number o…
cs.CR2020
Connecting Robust Shuffle Privacy and Pan-Privacy
Victor Balcer, Albert Cheu, Matthew Joseph +1
In the \emph{shuffle model} of differential privacy, data-holding users send randomized messages to a secure shuffler, the shuffler permutes the messages, and the resulting collect…
cs.CR2019
Separating Local & Shuffled Differential Privacy via Histograms
Victor Balcer, Albert Cheu
Recent work in differential privacy has highlighted the shuffled model as a promising avenue to compute accurate statistics while keeping raw data in users' hands. We present a pro…