On solving the densest k-subgraph problem on large graphs
Sotirov,Renata
Sotirov,Renata
Abstract
The densest k-subgraph problem is the problem of finding a k-vertex subgraph of a graph with the maximum number of edges. In order to solve large instances of the densest k-subgraph problem, we introduce two algorithms that are based on the random coordinate descent approach. Although it is common use to update at most two random coordinates simultaneously in each iteration of an algorithm, our algorithms may simultaneously update many coordinates. We show the benefit of updating more than two coordinates simultaneously for solving the densest k-subgraph problem, and solve large problem instances with up to 2 15 vertives. vertices.
Description
Publisher Copyright: © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Date
2020-12
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
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Journal Issue
Keywords
densest k-subgraph problem, random coordinate descent algorithm, large graphs
Citation
Sotirov, R 2020, 'On solving the densest k-subgraph problem on large graphs', Optimization Methods & Software, vol. 35, no. 6, pp. 1160-1178. https://doi.org/10.1080/10556788.2019.1595620