3,461 research outputs found
Small grid embeddings of 3-polytopes
We introduce an algorithm that embeds a given 3-connected planar graph as a
convex 3-polytope with integer coordinates. The size of the coordinates is
bounded by . If the graph contains a triangle we can
bound the integer coordinates by . If the graph contains a
quadrilateral we can bound the integer coordinates by . The
crucial part of the algorithm is to find a convex plane embedding whose edges
can be weighted such that the sum of the weighted edges, seen as vectors,
cancel at every point. It is well known that this can be guaranteed for the
interior vertices by applying a technique of Tutte. We show how to extend
Tutte's ideas to construct a plane embedding where the weighted vector sums
cancel also on the vertices of the boundary face
On the Properties of Gromov Matrices and their Applications in Network Inference
The spanning tree heuristic is a commonly adopted procedure in network
inference and estimation. It allows one to generalize an inference method
developed for trees, which is usually based on a statistically rigorous
approach, to a heuristic procedure for general graphs by (usually randomly)
choosing a spanning tree in the graph to apply the approach developed for
trees. However, there are an intractable number of spanning trees in a dense
graph. In this paper, we represent a weighted tree with a matrix, which we call
a Gromov matrix. We propose a method that constructs a family of Gromov
matrices using convex combinations, which can be used for inference and
estimation instead of a randomly selected spanning tree. This procedure
increases the size of the candidate set and hence enhances the performance of
the classical spanning tree heuristic. On the other hand, our new scheme is
based on simple algebraic constructions using matrices, and hence is still
computationally tractable. We discuss some applications on network inference
and estimation to demonstrate the usefulness of the proposed method
Communication tree problems
In this paper, we consider random communication
requirements and several cost
measures for a particular model of tree routing on a
complete network. First
we show that a random tree does not give any approximation.
Then give
approximation algorithms for the case for two random models
of requirements.Postprint (published version
- …