scispace - formally typeset
Open AccessJournal ArticleDOI

ź-nets and simplex range queries

TLDR
The concept of an ɛ-net of a set of points for an abstract set of ranges is introduced and sufficient conditions that a random sample is an Â-net with any desired probability are given.
Abstract
We demonstrate the existence of data structures for half-space and simplex range queries on finite point sets ind-dimensional space,dÂ?2, with linear storage andO(nÂ?) query time, $$\alpha = \frac{{d(d - 1)}}{{d(d - 1) + 1}} + \gamma for all \gamma > 0$$ . These bounds are better than those previously published for alldÂ?2. Based on ideas due to Vapnik and Chervonenkis, we introduce the concept of an Â?-net of a set of points for an abstract set of ranges and give sufficient conditions that a random sample is an Â?-net with any desired probability. Using these results, we demonstrate how random samples can be used to build a partition-tree structure that achieves the above query time.

read more

Content maybe subject to copyright    Report

Citations
More filters
Proceedings ArticleDOI

Visualization of Big Spatial Data using Coresets for Kernel Density Estimates

TL;DR: A method for subsampling of spatial data suitable for creating kernel density estimates from very large data is described and it is demonstrated that it results in less error than random sampling.

Product Range Spaces, Sensitive Sampling, and Derandomization

TL;DR: The concept of a sensitive E-approximation is introduced, and by extending the method to the intersection of a set of balls with the same radius, an O(n log3 n) deterministic algorithm for computing the diameter of an n-point set in 3-dimensional space is obtained.
Proceedings ArticleDOI

Small-size relative (p,ε)-approximations for well-behaved range spaces

TL;DR: Improved upper bounds for the size of relative (p,ε)-approximation for range spaces with the following property are presented: For any (finite) range space projected onto a ground set of size n and for any parameter 1 ≤ k ≤ n, the number of ranges of size at most k is only nearly-linear in n and polynomial in k.
Journal ArticleDOI

An Efficient Randomized Algorithm for Higher-Order Abstract Voronoi Diagrams

TL;DR: This study study covers many concrete order-k Voronoi diagrams defined by an abstract bisecting curve system that satisfies several practical axioms, and proposes a randomized incremental construction algorithm that runs in O(k(n-k)log2n+nlog3n) steps.
References
More filters
Book ChapterDOI

On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities

TL;DR: This chapter reproduces the English translation by B. Seckler of the paper by Vapnik and Chervonenkis in which they gave proofs for the innovative results they had obtained in a draft form in July 1966 and announced in 1968 in their note in Soviet Mathematics Doklady.
Book

Algorithms in Combinatorial Geometry

TL;DR: This book offers a modern approach to computational geo- metry, an area thatstudies the computational complexity of geometric problems with an important role in this study.
Journal ArticleDOI

On the density of families of sets

TL;DR: This paper will answer the question in the affirmative by determining the exact upper bound of T if T is a family of subsets of some infinite set S then either there exists to each number n a set A ⊂ S with |A| = n such that |T ∩ A| = 2n or there exists some number N such that •A| c for each A⩾ N and some constant c.
Journal ArticleDOI

Central Limit Theorems for Empirical Measures

TL;DR: In this article, the convergence of a stochastic process indexed by a Gaussian process to a certain Gaussian processes indexed by the supremum norm was studied in a Donsker class.
Journal ArticleDOI

The power of geometric duality

TL;DR: A new formulation of the notion of duality that allows the unified treatment of a number of geometric problems is used, to solve two long-standing problems of computational geometry and to obtain a quadratic algorithm for computing the minimum-area triangle with vertices chosen amongn points in the plane.