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1 code implementation • 26 Jan 2021 • Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri

Given a set of points $S$ and a radius parameter $r>0$, the $r$-near neighbor ($r$-NN) problem asks for a data structure that, given any query point $q$, returns a point $p$ within distance at most $r$ from $q$.

no code implementations • NeurIPS 2019 • Sariel Har-Peled, Sepideh Mahabadi

Namely, given a set of $n$ points $P$ and a parameter $r$, the goal is to preprocess the points, such that given a query point $q$, any point in the $r$-neighborhood of the query, i. e., $\ball(q, r)$, have the same probability of being reported as the near neighbor.

no code implementations • 9 Jul 2015 • Avrim Blum, Sariel Har-Peled, Benjamin Raichel

]{#1\left({#2}\right)} \newcommand{\npoints}{n} \newcommand{\ballD}{\mathsf{b}} \newcommand{\dataset}{{P}} $ For a set $\dataset$ of $\npoints$ points in the unit ball $\ballD \subseteq \Re^d$, consider the problem of finding a small subset $\algset \subseteq \dataset$ such that its convex-hull $\eps$-approximates the convex-hull of the original set.

no code implementations • 6 Jul 2015 • Sariel Har-Peled

In this note, we revisit the algorithm of Har-Peled et.

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