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39
DavenportSchinzel Sequences and Their Geometric Applications
, 1998
"... An (n; s) DavenportSchinzel sequence, for positive integers n and s, is a sequence composed of n distinct symbols with the properties that no two adjacent elements are equal, and that it does not contain, as a (possibly noncontiguous) subsequence, any alternation a \Delta \Delta \Delta b \Delta \ ..."
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Cited by 416 (115 self)
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An (n; s) DavenportSchinzel sequence, for positive integers n and s, is a sequence composed of n distinct symbols with the properties that no two adjacent elements are equal, and that it does not contain, as a (possibly noncontiguous) subsequence, any alternation a \Delta \Delta \Delta b \Delta \Delta \Delta a \Delta \Delta \Delta b \Delta \Delta \Delta of length s + 2 between two distinct symbols a and b. The close relationship between DavenportSchinzel sequences and the combinatorial structure of lower envelopes of collections of functions make the sequences very attractive because a variety of geometric problems can be formulated in terms of lower envelopes. A nearlinear bound on the maximum length of DavenportSchinzel sequences enable us to derive sharp bounds on the combinatorial structure underlying various geometric problems, which in turn yields efficient algorithms for these problems.
Arrangements and Their Applications
 Handbook of Computational Geometry
, 1998
"... The arrangement of a finite collection of geometric objects is the decomposition of the space into connected cells induced by them. We survey combinatorial and algorithmic properties of arrangements of arcs in the plane and of surface patches in higher dimensions. We present many applications of arr ..."
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Cited by 75 (20 self)
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The arrangement of a finite collection of geometric objects is the decomposition of the space into connected cells induced by them. We survey combinatorial and algorithmic properties of arrangements of arcs in the plane and of surface patches in higher dimensions. We present many applications of arrangements to problems in motion planning, visualization, range searching, molecular modeling, and geometric optimization. Some results involving planar arrangements of arcs have been presented in a companion chapter in this book, and are extended in this chapter to higher dimensions. Work by P.A. was supported by Army Research Office MURI grant DAAH049610013, by a Sloan fellowship, by an NYI award, and by a grant from the U.S.Israeli Binational Science Foundation. Work by M.S. was supported by NSF Grants CCR9122103 and CCR9311127, by a MaxPlanck Research Award, and by grants from the U.S.Israeli Binational Science Foundation, the Israel Science Fund administered by the Israeli Ac...
Point Sets With Many KSets
, 1999
"... For any n, k, n 2k > 0, we construct a set of n points in the plane with ne p log k ksets. This improves the bounds of Erd}os, Lovasz, et al. As a consequence, we also improve the lower bound of Edelsbrunner for the number of halving hyperplanes in higher dimensions. 1 Introduction For a ..."
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Cited by 43 (0 self)
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For any n, k, n 2k > 0, we construct a set of n points in the plane with ne p log k ksets. This improves the bounds of Erd}os, Lovasz, et al. As a consequence, we also improve the lower bound of Edelsbrunner for the number of halving hyperplanes in higher dimensions. 1 Introduction For a set P of n points in the ddimensional space, a kset is subset P 0 P such that P 0 = P \H for some halfspace H, and jP 0 j = k. The problem is to determine the maximum number of ksets of an npoint set in the ddimensional space. Even in the most studied two dimensional case, we are very far from the solution, and in higher dimensions even much less is known. The rst results in the two dimensional case are due to Erd}os, Lovasz, Simmons and Straus [L71], [ELSS73]. They established an upper bound O(n p k), and a lower bound (n log k). Despite great interest in this problem [W86], [E87], [S91], [EVW97], [AACS98], partly due to its importance in the analysis of geometric alg...
Constructing Levels in Arrangements and Higher Order Voronoi Diagrams
 SIAM J. COMPUT
, 1994
"... We give simple randomized incremental algorithms for computing the klevel in an arrangement of n hyperplanes in two and threedimensional space. The expected running time of our algorithms is O(nk+nff(n) log n) for the planar case, and O(nk 2 +n log 3 n) for the threedimensional case. Both bo ..."
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Cited by 42 (10 self)
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We give simple randomized incremental algorithms for computing the klevel in an arrangement of n hyperplanes in two and threedimensional space. The expected running time of our algorithms is O(nk+nff(n) log n) for the planar case, and O(nk 2 +n log 3 n) for the threedimensional case. Both bounds are optimal unless k is very small. The algorithm generalizes to computing the klevel in an arrangement of discs or xmonotone Jordan curves in the plane. Our approach can also be used to compute the klevel; this yields a randomized algorithm for computing the orderk Voronoi diagram of n points in the plane in expected time O(k(n \Gamma k) log n + n log 3 n).
Results on kSets and jFacets via Continuous Motion
"... Let be a set of points in in general position, i.e., no points on a commonflat,. Aset of is a set of points in that can be separated from by a hyperplane. Afacet of is an orientedsimplex spanned by points in which has exactly points from on the positive side of its affine hull. If is a planar po ..."
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Cited by 35 (9 self)
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Let be a set of points in in general position, i.e., no points on a commonflat,. Aset of is a set of points in that can be separated from by a hyperplane. Afacet of is an orientedsimplex spanned by points in which has exactly points from on the positive side of its affine hull. If is a planar point set and is even, a halving edge is an undirected edge between two points, such that the connecting line has the same number of points on either side. The number! "$ # ofsets is twice the number of halving edges. Inspired by Dey’s recent proof of a new bound on the number ofsets we show that
Clustering for EdgeCost Minimization
"... Leonard J. Schulman College of Computing Georgia Institute of Technology Atlanta GA 303320280 ABSTRACT We address the problem of partitioning a set of n points into clusters, so as to minimize the sum, over all intracluster pairs of points, of the cost associated with each pair. We obtain a ra ..."
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Cited by 30 (4 self)
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Leonard J. Schulman College of Computing Georgia Institute of Technology Atlanta GA 303320280 ABSTRACT We address the problem of partitioning a set of n points into clusters, so as to minimize the sum, over all intracluster pairs of points, of the cost associated with each pair. We obtain a randomized approximation algorithm for this problem, for the cost functions ` 2 2 ; `1 and `2 , as well as any cost function isometrically embeddable in ` 2 2 .
Extremal Problems for Geometric Hypergraphs
 Discrete Comput. Geom
, 1998
"... A geometric hypergraph H is a collection of idimensional simplices, called hyperedges or, simply, edges, induced by some (i + 1)tuples of a vertex set V in general position in dspace. The topological structure of geometric graphs, i.e., the case d = 2; i = 1, has been studied extensively, and it ..."
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Cited by 23 (2 self)
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A geometric hypergraph H is a collection of idimensional simplices, called hyperedges or, simply, edges, induced by some (i + 1)tuples of a vertex set V in general position in dspace. The topological structure of geometric graphs, i.e., the case d = 2; i = 1, has been studied extensively, and it proved to be instrumental for the solution of a wide range of problems in combinatorial and computational geometry. They include the kset problem, proximity questions, bounding the number of incidences between points and lines, designing various efficient graph drawing algorithms, etc. In this paper, we make an attempt to generalize some of these tools to higher dimensions. We will mainly consider extremal problems of the following type. What is the largest number of edges (isimplices) that a geometric hypergraph of n vertices can have without containing certain forbidden configurations? In particular, we discuss the special cases when the forbidden configurations are k intersecting edges...
On Levels in Arrangements of Curves
 Proc. 41st IEEE
, 2002
"... Analyzing the worstcase complexity of the klevel in a planar arrangement of n curves is a fundamental problem in combinatorial geometry. We give the first subquadratic upper bound (roughly O(nk 9 2 s 3 )) for curves that are graphs of polynomial functions of an arbitrary fixed degree s. Previously ..."
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Cited by 20 (3 self)
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Analyzing the worstcase complexity of the klevel in a planar arrangement of n curves is a fundamental problem in combinatorial geometry. We give the first subquadratic upper bound (roughly O(nk 9 2 s 3 )) for curves that are graphs of polynomial functions of an arbitrary fixed degree s. Previously, nontrivial results were known only for the case s = 1 and s = 2. We also improve the earlier bound for pseudoparabolas (curves that pairwise intersect at most twice) to O(nk k). The proofs are simple and rely on a theorem of Tamaki and Tokuyama on cutting pseudoparabolas into pseudosegments, as well as a new observation for cutting pseudosegments into pieces that can be extended to pseudolines. We mention applications to parametric and kinetic minimum spanning trees.
On the number of halving planes
 Combinatorica
, 1990
"... Let S ⊂ IR 3 be an nset in general position. A plane containing three of the points is called a halving plane if it dissects S into two parts of equal cardinality. It is proved that the number of halving planes is at most O(n 2.998). As a main tool, for every set Y of n points in the plane a set N ..."
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Cited by 20 (0 self)
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Let S ⊂ IR 3 be an nset in general position. A plane containing three of the points is called a halving plane if it dissects S into two parts of equal cardinality. It is proved that the number of halving planes is at most O(n 2.998). As a main tool, for every set Y of n points in the plane a set N of size O(n 4) is constructed such that the points of N are distributed almost evenly in the triangles determined by Y. 1 HALVING PLANES A pointset S ⊂ IR d is in general position if no d + 1 points of it lie in a hyperplane. The plane determined by the noncollinear points a, b, c is denoted by P (a, b, c). In general, the affine subspace spanned by the set A is denoted by aff(A). As usual, conv(A) stands for the convex hull of A. Assume that S is an nelement pointset in the threedimensional Euclidean space in general position. (i.e., no four of them are coplanar). A plane P (a, b, c), where a, b, c ∈ S, is called a halving plane if it dissects S into two equal parts, that is, on both sides of P there are exactly 1 2 (n − 3) points of S. Denote the number of halving planes by h(S), and set h(n) = max{h(S) : S ⊂ IR 3, S  = n, S is in general position}. Clearly, h(n) ≤ � � � � n 1 n 3. Moreover, h(n) ≥ 3 2, as any two points are contained in a halving plane. The aim of this paper is to improve these trivial bounds proving Theorem 1.1 Ω(n 2 log n) ≤ h(n) ≤ O(n 2.998).
Improved Bounds on Planar ksets and klevels
 Discrete Comput. Geom
, 1997
"... We prove an O(nk 1=3 ) upper bound for planar ksets. This is the first considerable improvement on this bound after its early solutions approximately twenty seven years ago. Our proof technique also applies to improve the current bounds on the combinatorial complexities of klevels in arrangement ..."
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Cited by 16 (0 self)
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We prove an O(nk 1=3 ) upper bound for planar ksets. This is the first considerable improvement on this bound after its early solutions approximately twenty seven years ago. Our proof technique also applies to improve the current bounds on the combinatorial complexities of klevels in arrangements of line segments, k convex polygons in the union of n lines, parametric minimum spanning trees and parametric matroids in general. 1 Introduction The problem of determining the optimum asymptotic bound on the number of ksets is one of the most tantalizing open problems in combinatorial geometry. Due to its importance in analyzing geometric algorithms [8, 9, 18], the problem has caught the attention of the computational geometers as well [5, 6, 7, 13, 17, 26, 28]. Given a set P of n points in ! d , and a positive integer k n, a kset is a subset P 0 ` P such that P 0 = P " H for a halfspace H and jP 0 j = k. A close to optimal solution for the problem remains elusive even in ! ...