Figure 3

Computational complexity of the G raphAlignment and G ræmlin algorithms. The scaling parameters estimated from the best power law fit of the data are given in the panels for the scenarios (i-iii). While the computational cost of G raphAlignment remains constant in all the scenarios, G ræmlin’s performance deteriorates with addition of spurious weak vertex similarities in scenario (iii).