The paper “A scalable distributed dynamical systems approach to learn the strongly connected components and diameter of networks”, authored by LASIGE’s integrated researcher Guilherme Ramos has been published in Transactions on Automatic Control (TAC), a top-ranked journal (Impact factor: 6.116; Scimago Q1). The paper co-authors are Emily Reed (University of Southern California, USA), Paul Bogdan (University of Southern California, USA) and Sérgio Pequito (Delft University of Technology).
Finding strongly connected components (SCCs) and the diameter of a directed network play a key role in a variety of machine learning and control theory problems. In this paper, the researchers provide for the first time a scalable distributed solution for these two problems by leveraging dynamical consensus-like protocols to find the SCCs.
The paper is available here.