Optimizing network robustness via Krylov subspaces
ESAIM: Mathematical Modelling and Numerical Analysis, vol. 58, pp. 131–155, 2024
We consider the problem of attaining either the maximal increase or reduction of the robustness of a complex network by means of a bounded modification of a subset of the edge weights. We propose two novel strategies combining Krylov subspace approximations with a greedy scheme and with the limited-memory BFGS. The …
On the stability of network indices defined by means of matrix functions
SIAM Journal on Matrix Analysis and Applications, vol. 39, pp. 1521–1546, 2018
Identifying important components in a network is one of the major goals of network analysis. Popular and effective measures of importance of a node or a set of nodes are defined in terms of suitable entries of functions of matrices $f(A)$. These kinds of measures are particularly relevant as they are able to capture …