28 citations · 174 across the 52 of their papers we have counts for
5 papers · 1 filter
On Differentially Private Linear Algebra
Haim Kaplan, Yishay Mansour, Shay Moran +2
We introduce efficient differentially private (DP) algorithms for several linear algebraic tasks, including solving linear equalities over arbitrary fields, linear inequalities ove…
One Attack to Rule Them All: Tight Quadratic Bounds for Adaptive Queries on Cardinality Sketches
Edith Cohen, Jelani Nelson, Tamás Sarlós +2
Cardinality sketches are compact data structures for representing sets or vectors. These sketches are space-efficient, typically requiring only logarithmic storage in the input siz…
Data Reconstruction: When You See It and When You Don't
Edith Cohen, Haim Kaplan, Yishay Mansour +4
We revisit the fundamental question of formally defining what constitutes a reconstruction attack. While often clear from the context, our exploration reveals that a precise defini…
Lower Bounds for Differential Privacy Under Continual Observation and Online Threshold Queries
Edith Cohen, Xin Lyu, Jelani Nelson +2
One of the most basic problems for studying the "price of privacy over time" is the so called private counter problem, introduced by Dwork et al. (2010) and Chan et al. (2010). In…
Private Truly-Everlasting Robust-Prediction
Uri Stemmer
Private Everlasting Prediction (PEP), recently introduced by Naor et al. [2023], is a model for differentially private learning in which the learner never publicly releases a hypot…