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The Power of Linear-Time Data Reduction for Maximum Matching

Mertzios, G.B.; Nichterlein, A.; Niedermeier, R.

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Authors

A. Nichterlein

R. Niedermeier



Contributors

Kim G. Larsen
Editor

Hans L. Bodlaender
Editor

Jean-Francois Raskin
Editor

Abstract

Finding maximum-cardinality matchings in undirected graphs is arguably one of the most central graph primitives. For m-edge and n-vertex graphs, it is well-known to be solvable in O(m\sqrt{n}) time; however, for several applications this running time is still too slow. We investigate how linear-time (and almost linear-time) data reduction (used as preprocessing) can alleviate the situation. More specifically, we focus on linear-time kernelization. We start a deeper and systematic study both for general graphs and for bipartite graphs. Our data reduction algorithms easily comply (in form of preprocessing) with every solution strategy (exact, approximate, heuristic), thus making them attractive in various settings.

Citation

Mertzios, G., Nichterlein, A., & Niedermeier, R. (2017). The Power of Linear-Time Data Reduction for Maximum Matching. In K. G. Larsen, H. L. Bodlaender, & J. Raskin (Eds.), 42nd International Symposium on Mathematical Foundations of Computer Science (MFCS 2017) : August 21-25, 2017, Aalborg (Denmark) ; proceedings. https://doi.org/10.4230/lipics.mfcs.2017.46

Conference Name 42nd International Symposium on Mathematical Foundations of Computer Science (MFCS).
Conference Location Aalborg, Denmark
Start Date Aug 21, 2017
End Date Aug 25, 2017
Acceptance Date Jun 12, 2017
Online Publication Date Nov 1, 2017
Publication Date Dec 1, 2017
Deposit Date Jun 26, 2017
Publicly Available Date Mar 29, 2024
Series Title LIPIcs–Leibniz International Proceedings in Informatics
Series Number 83
Series ISSN 1868-8969
Book Title 42nd International Symposium on Mathematical Foundations of Computer Science (MFCS 2017) : August 21-25, 2017, Aalborg (Denmark) ; proceedings.
DOI https://doi.org/10.4230/lipics.mfcs.2017.46
Public URL https://durham-repository.worktribe.com/output/1146058

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