Counting small cuts in a graph
Data Structures and Algorithms
2013-04-30 v1
Abstract
We study the minimum cut problem in the presence of uncertainty and show how to apply a novel robust optimization approach, which aims to exploit the similarity in subsequent graph measurements or similar graph instances, without posing any assumptions on the way they have been obtained. With experiments we show that the approach works well when compared to other approaches that are also oblivious towards the relationship between the input datasets.
Keywords
Cite
@article{arxiv.1304.7632,
title = {Counting small cuts in a graph},
author = {Barbara Geissmann and Rastislav Šrámek},
journal= {arXiv preprint arXiv:1304.7632},
year = {2013}
}