Range Counting Oracles for Geometric Problems

Fuente: arXiv
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Hauptverfasser: Driemel, Anne, Monemizadeh, Morteza, Oh, Eunjin, Staals, Frank, Woodruff, David P.
Format: Preprint
Veröffentlicht: 2025
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author Driemel, Anne
Monemizadeh, Morteza
Oh, Eunjin
Staals, Frank
Woodruff, David P.
author_facet Driemel, Anne
Monemizadeh, Morteza
Oh, Eunjin
Staals, Frank
Woodruff, David P.
contents In this paper, we study estimators for geometric optimization problems in the sublinear geometric model. In this model, we have oracle access to a point set with size $n$ in a discrete space $[Δ]^d$, where queries can be made to an oracle that responds to orthogonal range counting requests. The query complexity of an optimization problem is measured by the number of oracle queries required to compute an estimator for the problem. We investigate two problems in this framework, the Euclidean Minimum Spanning Tree (MST) and Earth Mover Distance (EMD). For EMD, we show the existence of an estimator that approximates the cost of EMD with $O(\log Δ)$-relative error and $O(\frac{nΔ}{s^{1+1/d}})$-additive error using $O(s\polylog Δ)$ range counting queries for any parameter $s$ with $1\leq s \leq n$. Moreover, we prove that this bound is tight. For MST, we demonstrate that the weight of MST can be estimated within a factor of $(1 \pm \eps)$ using $\tilde{O}(\sqrt{n})$ range counting queries.
format Preprint
id arxiv_https___arxiv_org_abs_2504_15292
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Range Counting Oracles for Geometric Problems
Driemel, Anne
Monemizadeh, Morteza
Oh, Eunjin
Staals, Frank
Woodruff, David P.
Computational Geometry
Data Structures and Algorithms
In this paper, we study estimators for geometric optimization problems in the sublinear geometric model. In this model, we have oracle access to a point set with size $n$ in a discrete space $[Δ]^d$, where queries can be made to an oracle that responds to orthogonal range counting requests. The query complexity of an optimization problem is measured by the number of oracle queries required to compute an estimator for the problem. We investigate two problems in this framework, the Euclidean Minimum Spanning Tree (MST) and Earth Mover Distance (EMD). For EMD, we show the existence of an estimator that approximates the cost of EMD with $O(\log Δ)$-relative error and $O(\frac{nΔ}{s^{1+1/d}})$-additive error using $O(s\polylog Δ)$ range counting queries for any parameter $s$ with $1\leq s \leq n$. Moreover, we prove that this bound is tight. For MST, we demonstrate that the weight of MST can be estimated within a factor of $(1 \pm \eps)$ using $\tilde{O}(\sqrt{n})$ range counting queries.
title Range Counting Oracles for Geometric Problems
topic Computational Geometry
Data Structures and Algorithms
url https://arxiv.org/abs/2504.15292