no code implementations • 19 Jul 2023 • Harald Semmelrock, Simone Kopeinik, Dieter Theiler, Tony Ross-Hellauer, Dominik Kowald
Research is facing a reproducibility crisis, in which the results and findings of many studies are difficult or even impossible to reproduce.
no code implementations • 7 Feb 2023 • Sebastian Scher, Bernhard Geiger, Simone Kopeinik, Andreas Trügler, Dominik Kowald
For a long time, machine learning (ML) has been seen as the abstract problem of learning relationships from data independent of the surrounding settings.
no code implementations • 17 Aug 2022 • Sebastian Scher, Simone Kopeinik, Andreas Trügler, Dominik Kowald
We conclude that in order to quantify the trade-off correctly and to assess the long-term fairness effects of such a system in the real-world, careful modeling of the surrounding labor market is indispensable.
1 code implementation • 28 Apr 2021 • Navid Rekabsaz, Simone Kopeinik, Markus Schedl
In this work, we first provide a novel framework to measure the fairness in the retrieved text contents of ranking models.
1 code implementation • 30 Jan 2015 • Paul Seitlinger, Dominik Kowald, Simone Kopeinik, Ilire Hasani-Mavriqi, Tobias Ley, Elisabeth Lex
Classic resource recommenders like Collaborative Filtering (CF) treat users as being just another entity, neglecting non-linear user-resource dynamics shaping attention and interpretation.