28 citations · 244 across the 83 of their papers we have counts for
9 papers · 1 filter
The Sparse Vector Technique, Revisited
Haim Kaplan, Yishay Mansour, Uri Stemmer
We revisit one of the most basic and widely applicable techniques in the literature of differential privacy - the sparse vector technique [Dwork et al., STOC 2009]. This simple alg…
Duality-based approximation algorithms for depth queries and maximum depth
Dror Aiger, Haim Kaplan, Micha Sharir
We design an efficient data structure for computing a suitably defined approximate depth of any query point in the arrangement of a collection of halfplane…
Output sensitive algorithms for approximate incidences and their applications
Dror Aiger, Haim Kaplan, Micha Sharir
An -approximate incidence between a point and some geometric object (line, circle, plane, sphere) occurs when the point and the object lie at distance at most from each othe…
On Radial Isotropic Position: Theory and Algorithms
Shiri Artstein-Avidan, Haim Kaplan, Micha Sharir
We review the theory of, and develop algorithms for transforming a finite point set in into a set in \emph{radial isotropic position} by a nonsingular linear transforma…
Locality Sensitive Hashing for Set-Queries, Motivated by Group Recommendations
Haim Kaplan, Jay Tenenbaum
Locality Sensitive Hashing (LSH) is an effective method to index a set of points such that we can efficiently find the nearest neighbors of a query point. We extend this method to…
Adversarially Robust Streaming Algorithms via Differential Privacy
Avinatan Hassidim, Haim Kaplan, Yishay Mansour +2
A streaming algorithm is said to be adversarially robust if its accuracy guarantees are maintained even when the data stream is chosen maliciously, by an adaptive adversary. We est…