65 citations · 262 across the 38 of their papers we have counts for
49 papers
Differentially Private Aggregation via Imperfect Shuffling
Badih Ghazi, Ravi Kumar, Pasin Manurangsi +2
In this paper, we introduce the imperfect shuffle differential privacy model, where messages sent from users are shuffled in an almost uniform manner before being observed by a cur…
Fast Optimal Locally Private Mean Estimation via Random Projections
Hilal Asi, Vitaly Feldman, Jelani Nelson +2
We study the problem of locally private mean estimation of high-dimensional vectors in the Euclidean ball. Existing algorithms for this problem either incur sub-optimal error or ha…
Sparse Dimensionality Reduction Revisited
Mikael Møller Høgsgaard, Lion Kamma, Kasper Green Larsen +2
The sparse Johnson-Lindenstrauss transform is one of the central techniques in dimensionality reduction. It supports embedding a set of points in into $m=O(\vare…
Private Counting of Distinct and k-Occurring Items in Time Windows
Badih Ghazi, Ravi Kumar, Pasin Manurangsi +1
In this work, we study the task of estimating the numbers of distinct and -occurring items in a time window under the constraint of differential privacy (DP). We consider severa…
Õptimal Differentially Private Learning of Thresholds and Quasi-Concave Optimization
Edith Cohen, Xin Lyu, Jelani Nelson +2
The problem of learning threshold functions is a fundamental one in machine learning. Classical learning theory implies sample complexity of (for generalizati…
On the amortized complexity of approximate counting
Ishaq Aden-Ali, Yanjun Han, Jelani Nelson +1
Naively storing a counter up to value would require bits of memory. Nelson and Yu [NY22], following work of [Morris78], showed that if the query answers need only b…