9 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.LG2025
The Benchmarking Epistemology: Validity Theory for Evaluating Machine Learning Models
Timo Freiesleben, Sebastian Zezulka
Predictive benchmarking, evaluating machine learning models based on predictive performance and competitive ranking, is central to machine learning research and scientific inquiry.…
cs.CY2024★ 9 cited
From the Fair Distribution of Predictions to the Fair Distribution of Social Goods: Evaluating the Impact of Fair Machine Learning on Long-Term Unemployment
Sebastian Zezulka, Konstantin Genin
Deploying an algorithmically informed policy is a significant intervention in society. Prominent methods for algorithmic fairness focus on the distribution of predictions at the ti…
cs.CY2023★ 1 cited
Performativity and Prospective Fairness
Sebastian Zezulka, Konstantin Genin
Deploying an algorithmically informed policy is a significant intervention in the structure of society. As is increasingly acknowledged, predictive algorithms have performative eff…