Counting small cuts in a graph [article]

Barbara Geissmann, Rastislav Šrámek
2013 arXiv   pre-print
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.
arXiv:1304.7632v1 fatcat:serabego65bxzhcwub6xpibkaa