1 code implementation • 2 Sep 2015 • Sebastian Lamm, Peter Sanders, Christian Schulz, Darren Strash, Renato F. Werneck
To avoid this problem, we recursively choose vertices that are likely to be in a large independent set (using an evolutionary approach), then further kernelize the graph.
no code implementations • 20 Apr 2015 • Hannah Bast, Daniel Delling, Andrew Goldberg, Matthias Müller-Hannemann, Thomas Pajor, Peter Sanders, Dorothea Wagner, Renato F. Werneck
We survey recent advances in algorithms for route planning in transportation networks.
Data Structures and Algorithms G.2.1; G.2.2; G.2.3; H.2.8; H.3.5; H.4.2
no code implementations • 26 Aug 2014 • Edith Cohen, Daniel Delling, Thomas Pajor, Renato F. Werneck
The gold standard for Influence Maximization is the greedy algorithm, which iteratively adds to the seed set a node maximizing the marginal gain in influence.
Data Structures and Algorithms Social and Information Networks G.2.2; H.2.8