On the Budgeted Hausdorff Distance Problem
Abstract: $ \newcommand{\Re}{\mathbb{R}} \newcommand{\reals}{\mathbb{R}} \newcommand{\SetX}{\mathsf{X}} \newcommand{\optX}[1]{#1<sup>\star}</sup> \newcommand{\Qopt}{\Mh{\optX{Q}}} \newcommand{\rad}{r} \newcommand{\Mh}[1]{#1} \newcommand{\query}{q} \newcommand{\eps}{\varepsilon} \newcommand{\VorX}[1]{\mathcal{V} \pth{#1}} \newcommand{Polygon}{\mathsf{P}} \newcommand{\IntRange}[1]{[ #1 ]} \newcommand{\Space}{\overline{\mathsf{m}}} \newcommand{\pth}[2][!]{#1\left({#2}\right)} \newcommand{\polylog}{\mathrm{polylog}} \newcommand{\N}{\mathbb N} \newcommand{\Z}{\mathbb Z} \newcommand{\pt}{p} \newcommand{\distY}[2]{\left| {#1} - {#2} \right|} \newcommand{\ptq}{q} \newcommand{\RunningTime}{O\bigl(n<sup>{3/2}</sup> \sqrt{k} \log<sup>{3/2}</sup> n + kn \log<sup>2</sup> n\bigr)} \newcommand{\pts}{s}$ Given a set of points in the plane, and a parameter , we present an algorithm, whose running time is $\RunningTime$, with high probability, that computes a subset $\Qopt \subseteq P$ of points, that minimizes the Hausdorff distance between the convex-hulls of $\Qopt$ and . This is the first subquadratic algorithm for this problem if is small.
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