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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.

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Optimal Approximations Made Easy

TL;DR: In this paper, the authors present a modular, self-contained, intuitive proof of the Chernoff's concentration bound for finite set systems, which can be covered in a single lecture in a geometry, algorithms, or combinatorics course.
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The VC-Dimension of Graphs with Respect to k-Connected Subgraphs

TL;DR: In this article, the VC-dimension of the set system on the vertex set of some graph which is induced by the family of its $k$-connected subgraphs was studied.
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The Visibility Center of a Simple Polygon

TL;DR: In this article, the problem of finding the visibility center of a set of points inside a polygon is reduced to finding the maximum geodesic distance from any point in the polygon to see any other point.
Book ChapterDOI

Using \(\epsilon \)-nets for Solving the Classification Problem

TL;DR: The proposed algorithm of solving the classification problem using the \(\epsilon \)-nets has the same computational complexity as Support Vector Machine \(O(n\ln n)\) and its accuracy is comparable with SVM results.
References
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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.