Section: New Results
Statistical Learning on Graphs
The main purpose of [11] is to illustrate that certain Hölder-type inequalities can
be employed in order to obtain concentration and correlation bounds for sums of weakly
dependent random variables whose dependencies are described in terms of graphs, or
hypergraphs. Let
where
Several collaborations concerned efficient counting of subgraph frequencies in networks. Two journal articles are accepted subject to minor revisions, one in collaboration with the group of Yvan Saeys (University of Ghent, Belgium), and one in collaboration with Irma Ravkic and Martin Znidarsic (former collaborators of Jan Ramon ).