AbstractLet S be a family of n points in Ed. The exact fitting problem is that of finding a hyperplane containing the maximum number of points of S. In this paper, we present an O(min{(ndmd−1)log(nm),nd}) time algorithm where m denotes the number of points in the hyperplane. This algorithm is based on upper bounds on the maximum number of incidences between families of points and families of hyperplanes in Ed and on and algorithm to compute these incidences. We also show how the upper bound on the maximum number of incidences between families of points and families of hyperplanes can be used to derive new bounds on some well-known problems in discrete geometry
The k-means algorithm is a well-known method for parti-tioning n points that lie in the d-dimensiona...
AbstractWe consider the problem of computing the diameter of a set of n points in d-dimensional Eucl...
AbstractIn this paper we consider a problem of distance selection in the arrangement of hyperplanes ...
AbstractLet S be a family of n points in Ed. The exact fitting problem is that of finding a hyperpla...
International audienceWe consider the following fitting problem: given an arbitrary set of N points ...
AbstractIn this paper we discuss three closely related problems on the incidence structure between n...
We investigate algorithmic questions that arise in the statistical problem of computing lines or hyp...
Consider the following problem: find the "best" approximating hyperplane for a family of points. The...
We establish new lower bounds on the complexity of the following basic geometric problem, attributed...
This paper describes novel and fast, simple and robust algorithm with O(N) expected complexity which...
AbstractWe present a solution to the point location problem in arrangements of hyperplanes in Ed wit...
We establish new lower bounds on the complexity of the following basic geometric problem, attributed...
A set of points and a positive integer m are given and our goal is to cover the maximum number of th...
International audienceThis paper addresses the hyperplane fitting problem of discrete points in any ...
Let d and k be integers with 1 0 is an arbitrarily small constant. This nearly settles a problem me...
The k-means algorithm is a well-known method for parti-tioning n points that lie in the d-dimensiona...
AbstractWe consider the problem of computing the diameter of a set of n points in d-dimensional Eucl...
AbstractIn this paper we consider a problem of distance selection in the arrangement of hyperplanes ...
AbstractLet S be a family of n points in Ed. The exact fitting problem is that of finding a hyperpla...
International audienceWe consider the following fitting problem: given an arbitrary set of N points ...
AbstractIn this paper we discuss three closely related problems on the incidence structure between n...
We investigate algorithmic questions that arise in the statistical problem of computing lines or hyp...
Consider the following problem: find the "best" approximating hyperplane for a family of points. The...
We establish new lower bounds on the complexity of the following basic geometric problem, attributed...
This paper describes novel and fast, simple and robust algorithm with O(N) expected complexity which...
AbstractWe present a solution to the point location problem in arrangements of hyperplanes in Ed wit...
We establish new lower bounds on the complexity of the following basic geometric problem, attributed...
A set of points and a positive integer m are given and our goal is to cover the maximum number of th...
International audienceThis paper addresses the hyperplane fitting problem of discrete points in any ...
Let d and k be integers with 1 0 is an arbitrarily small constant. This nearly settles a problem me...
The k-means algorithm is a well-known method for parti-tioning n points that lie in the d-dimensiona...
AbstractWe consider the problem of computing the diameter of a set of n points in d-dimensional Eucl...
AbstractIn this paper we consider a problem of distance selection in the arrangement of hyperplanes ...