We present a general technique for dynamizing certain problems posed on point sets in Euclidean space for any fixed dimension d. This technique applies to a large class of structurally similar algorithms, presented previously by the authors, that make use of the well-separated pair decomposition. We prove efficient worst-case complexity for maintaining such computations under point insertions and deletions, and apply the technique to several problems posed on a set P containing n points. In particular, we show how to answer a query for any point x that returns a constant-size set of points, a subset of which consists of all points in P that have x as a nearest neighbor. We then show how to use such queries to maintain the closest pair of p...
28th International Symposium on Computer and Information Sciences (ISCIS) -- OCT 28-29, 2013 -- Inst...
This dissertation develops and studies fast algorithms for solving closest point problems. Algorithm...
We develop data structures for dynamic closest pair problems with arbitrary (not necessarily geometr...
Abstract. We define the notion of a well-separated pair decomposition of points in d-dimensional spa...
Given a set S of n points in k-dimensional space, and an L t metric, the dynamic closest pair proble...
Abstract. We define the notion of a well-separated pair decomposition of points in d-dimensional spa...
One of the most challenging problems in computational geometry is closest pair of points given n poi...
We describe a new randomized data structure, the sparse partition, for solving the dynamic closest-p...
This is the preliminary version of a chapter that will appear in the Handbook on Computational Geome...
We describe a new randomized data structure, the {\em sparse partition}, for solving the dynamic clo...
In the $k$-dimensional rectangular point location problem, we have to store a set of $n$ non-overlap...
This is the preliminary version of a chapter that will appear in the Handbook on Computational Geome...
AbstractIn the k-dimensional rectangular point location problem, we have to store a set of n non-ove...
We present a conceptually simple, randomized incremental algorithm for finding the closest pair in a...
Given a set S of n points in k-dimensional space, and an Lt metric, the dynamic closest-pair problem...
28th International Symposium on Computer and Information Sciences (ISCIS) -- OCT 28-29, 2013 -- Inst...
This dissertation develops and studies fast algorithms for solving closest point problems. Algorithm...
We develop data structures for dynamic closest pair problems with arbitrary (not necessarily geometr...
Abstract. We define the notion of a well-separated pair decomposition of points in d-dimensional spa...
Given a set S of n points in k-dimensional space, and an L t metric, the dynamic closest pair proble...
Abstract. We define the notion of a well-separated pair decomposition of points in d-dimensional spa...
One of the most challenging problems in computational geometry is closest pair of points given n poi...
We describe a new randomized data structure, the sparse partition, for solving the dynamic closest-p...
This is the preliminary version of a chapter that will appear in the Handbook on Computational Geome...
We describe a new randomized data structure, the {\em sparse partition}, for solving the dynamic clo...
In the $k$-dimensional rectangular point location problem, we have to store a set of $n$ non-overlap...
This is the preliminary version of a chapter that will appear in the Handbook on Computational Geome...
AbstractIn the k-dimensional rectangular point location problem, we have to store a set of n non-ove...
We present a conceptually simple, randomized incremental algorithm for finding the closest pair in a...
Given a set S of n points in k-dimensional space, and an Lt metric, the dynamic closest-pair problem...
28th International Symposium on Computer and Information Sciences (ISCIS) -- OCT 28-29, 2013 -- Inst...
This dissertation develops and studies fast algorithms for solving closest point problems. Algorithm...
We develop data structures for dynamic closest pair problems with arbitrary (not necessarily geometr...