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Durham University

Computer Science


Publication details for Dr George Mertzios

Mertzios, G.B., Nichterlein, A. & Niedermeier, R. (2017), The Power of Linear-Time Data Reduction for Maximum Matching, in Larsen, Kim G., Bodlaender, Hans L. & Raskin, Jean-Francois eds, LIPIcs–Leibniz International Proceedings in Informatics 83: 42nd International Symposium on Mathematical Foundations of Computer Science (MFCS). Aalborg, Denmark, Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl, Germany, 46:1-46:14.

Author(s) from Durham


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.