We consider a variant of the k-center clustering problem in IRd, where the centers can be divided into two subsets—one, the red centers of size p, and the other, the blue centers of size q, such that p+q=k, and each red center and each blue center must be a distance of at least some given α≥0 apart. The aim is to minimize the covering radius. We provide a bi-criteria approximation algorithm for the problem and a polynomial time algorithm for the constrained problem where all centers must lie on a given line ℓ. Additionally, we present a polynomial time algorithm for the case where only the orientation of the line is fixed in the plane (d=2), although the algorithm works even in IRd by constraining the line to lie in a plane and with a fixed...
We study the LowerBoundedCenter (LBC) problem, which is a clustering problem that can be viewed as a...
AbstractIn k-means clustering we are given a set of n data points in d-dimensional space Rd and an i...
In this paper we present an n O(k 1\Gamma1=d ) time algorithm for solving the k-center problem i...
We study a generalization of k-center clustering, first introduced by Kavand et. al., where instead ...
An instance of colorful k-center consists of points in a metric space that are colored red or blue, ...
Introduction Clustering is an important problem, with applications in areas such as data mining and...
Clustering is an important problem and has numerous applications. In this paper we consider an impor...
In this thesis we show that, for several clustering problems, we can extract a small set of points, ...
Motivated by an application from geodesy, we introduce a novel clustering problem which is a $k$-cen...
AbstractTwo complications frequently arise in real-world applications, motion and the contamination ...
The Euclidean $k$-center problem is a classical problem that has been extensively studied in compute...
Families of center-based clustering methods are capable of handling high dimensional sparse data ari...
A practical problem that requires the classification of a set of points of IR using a criterion ...
In this paper, we show that for several clustering problems one can extract a small set of points, s...
<p>In the first part of this chapter we detail center based clustering methods, namely methods based...
We study the LowerBoundedCenter (LBC) problem, which is a clustering problem that can be viewed as a...
AbstractIn k-means clustering we are given a set of n data points in d-dimensional space Rd and an i...
In this paper we present an n O(k 1\Gamma1=d ) time algorithm for solving the k-center problem i...
We study a generalization of k-center clustering, first introduced by Kavand et. al., where instead ...
An instance of colorful k-center consists of points in a metric space that are colored red or blue, ...
Introduction Clustering is an important problem, with applications in areas such as data mining and...
Clustering is an important problem and has numerous applications. In this paper we consider an impor...
In this thesis we show that, for several clustering problems, we can extract a small set of points, ...
Motivated by an application from geodesy, we introduce a novel clustering problem which is a $k$-cen...
AbstractTwo complications frequently arise in real-world applications, motion and the contamination ...
The Euclidean $k$-center problem is a classical problem that has been extensively studied in compute...
Families of center-based clustering methods are capable of handling high dimensional sparse data ari...
A practical problem that requires the classification of a set of points of IR using a criterion ...
In this paper, we show that for several clustering problems one can extract a small set of points, s...
<p>In the first part of this chapter we detail center based clustering methods, namely methods based...
We study the LowerBoundedCenter (LBC) problem, which is a clustering problem that can be viewed as a...
AbstractIn k-means clustering we are given a set of n data points in d-dimensional space Rd and an i...
In this paper we present an n O(k 1\Gamma1=d ) time algorithm for solving the k-center problem i...