no code implementations • NeurIPS 2021 • Róbert Busa-Fekete, Dimitris Fotakis, Emmanouil Zampetakis
We study the problem of uniformity testing for statistical data that consists of rankings over $m$ items where the alternative class is restricted to Mallows models with single parameter.
no code implementations • NeurIPS 2021 • Róbert Busa-Fekete, Dimitris Fotakis, Balazs Szorenyi, Emmanouil Zampetakis
In this paper, we devise identity tests for ranking data that is generated from Mallows model both in the \emph{asymptotic} and \emph{non-asymptotic} settings.
no code implementations • NeurIPS 2020 • Alessandro Epasto, Mohammad Mahdian, Vahab Mirrokni, Emmanouil Zampetakis
A soft-max function has two main efficiency measures: (1) approximation - which corresponds to how well it approximates the maximum function, (2) smoothness - which shows how sensitive it is to changes of its input.
