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20182024
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cs.DS2024

Efficient Uniform Negative Edge Weights

Lukas Geis, Daniel Allendorf, Thomas Bläsius +4

We consider a maximum entropy edge weight model that allows for negative weights. Given a graph and possible weights typically consisting of positive and negative…

cs.DS2022

Certifying Induced Subgraphs in Large Graphs

Ulrich Meyer, Hung Tran, Konstantinos Tsakalidis

We introduce I/O-optimal certifying algorithms for bipartite graphs, as well as for the classes of split, threshold, bipartite chain, and trivially perfect graphs. When the input g…

cs.DS2021

Engineering Uniform Sampling of Graphs with a Prescribed Power-law Degree Sequence

Daniel Allendorf, Ulrich Meyer, Manuel Penschuck +2

We consider the following common network analysis problem: given a degree sequence return a uniform sample from the ensemble of all…

cs.DS2020

Simulating Population Protocols in Sub-Constant Time per Interaction

Petra Berenbrink, David Hammer, Dominik Kaaser +3

We consider the problem of efficiently simulating population protocols. In the population model, we are given a distributed system of agents modeled as identical finite-state m…

cs.DS2018

Parallel and I/O-efficient Randomisation of Massive Networks using Global Curveball Trades

Corrie Jacobien Carstens, Michael Hamann, Ulrich Meyer +3

Graph randomisation is a crucial task in the analysis and synthesis of networks. It is typically implemented as an edge switching process (ESMC) repeatedly swapping the nodes of ra…