2 papers
cs.LG2024
A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective Landscapes
Jake Robertson, Thorsten Schmidt, Frank Hutter +1
Fairness-aware Machine Learning (FairML) applications are often characterized by complex social objectives and legal requirements, frequently involving multiple, potentially confli…
q-fin.RM2023
A novel scaling approach for unbiased adjustment of risk estimators
Marcin Pitera, Thorsten Schmidt, Łukasz Stettner
The assessment of risk based on historical data faces many challenges, in particular due to the limited amount of available data, lack of stationarity, and heavy tails. While estim…