3 accepted papers
Machine learning models are known to be susceptible to adversarial perturbations. Even more concerning is the fact that these adversarial perturbations can be found by black-box search using surprisingly few queries, which essentially restricts the perturbation to a subspace of dimension $k$—much sm…
As the issue of robustness in AI systems becomes vital, statistical learning techniques that are reliable even in presence of partly contaminated data have to be developed. Preference data, in the form of (complete) rankings in the simplest situations, are no exception and the demand for appropriate…
The concept of median/consensus has been widely investigated in order to provide a statistical summary of ranking data, i.e. realizations of a random permutation $\Sigma$ of a finite set, $\{1,; \ldots,;{n}\}$ with $n\geq 1$ say. As it sheds light onto only one aspect of $\Sigma$’s distribution $P$,…