Counting large patterns in degenerate graphs
Christine Awofeso, Patrick Greaves, Oded Lachish, Felix Reidl

TL;DR
This paper improves algorithms for counting large patterns in $d$-degenerate graphs by introducing the concept of $(c,d)$-locatable graphs, achieving more efficient runtimes with polynomial dependence on pattern size.
Contribution
The paper introduces $(c,d)$-locatable graphs, extending previous work, and provides improved algorithms with polynomial dependence on pattern size for counting subgraphs in $d$-degenerate graphs.
Findings
Improved subgraph counting algorithms for $(c,d)$-locatable graphs.
Characterization of $(1,d)$-locatable graphs with linear runtime dependence.
Lower bounds showing hardness for barely non-$(c,d)$-locatable graphs.
Abstract
The problem of subgraph counting asks for the number of occurrences of a pattern graph as a subgraph of a host graph and is known to be computationally challenging: it is -hard even when is restricted to simple structures such as cliques or paths. Curticapean and Marx (FOCS'14) show that if the graph has vertex cover number , subgraph counting has time complexity . This raises the question of whether this upper bound can be improved for input graphs from a restricted family of graphs. Earlier work by Eppstein~(IPL'94) shows that this is indeed possible, by proving that when is a -degenerate graph and is a biclique of arbitrary size, subgraph counting has time complexity . We show that if the input is restricted to -degenerate graphs, the upper bound of Curticapean and Marx can be…
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Taxonomy
TopicsGraph Theory and Algorithms · Advanced Graph Theory Research · Complex Network Analysis Techniques
