Open Problems in (Hyper)Graph Decomposition
Data Structures and Algorithms
2023-10-19 v1
Abstract
Large networks are useful in a wide range of applications. Sometimes problem instances are composed of billions of entities. Decomposing and analyzing these structures helps us gain new insights about our surroundings. Even if the final application concerns a different problem (such as traversal, finding paths, trees, and flows), decomposing large graphs is often an important subproblem for complexity reduction or parallelization. This report is a summary of discussions that happened at Dagstuhl seminar 23331 on "Recent Trends in Graph Decomposition" and presents currently open problems and future directions in the area of (hyper)graph decomposition.
Cite
@article{arxiv.2310.11812,
title = {Open Problems in (Hyper)Graph Decomposition},
author = {Deepak Ajwani and Rob H. Bisseling and Katrin Casel and Ümit V. Çatalyürek and Cédric Chevalier and Florian Chudigiewitsch and Marcelo Fonseca Faraj and Michael Fellows and Lars Gottesbüren and Tobias Heuer and George Karypis and Kamer Kaya and Jakub Lacki and Johannes Langguth and Xiaoye Sherry Li and Ruben Mayer and Johannes Meintrup and Yosuke Mizutani and François Pellegrini and Fabrizio Petrini and Frances Rosamond and Ilya Safro and Sebastian Schlag and Christian Schulz and Roohani Sharma and Darren Strash and Blair D. Sullivan and Bora Uçar and Albert-Jan Yzelman},
journal= {arXiv preprint arXiv:2310.11812},
year = {2023}
}