2 papers
cs.DL2026
Overcoming Barriers to Computational Reproducibility
Roman Hornung, László Németh, Oleksandr Zadorozhny +13
Computational reproducibility, the possibility for independent researchers to exactly reproduce published empirical results, is fundamental to science. Despite its importance, the…
stat.ML2025
Beyond algorithm hyperparameters: on preprocessing hyperparameters and associated pitfalls in machine learning applications
Christina Sauer, Anne-Laure Boulesteix, Luzia HanÃum +3
Adequately generating and evaluating prediction models based on supervised machine learning (ML) is often challenging, especially for less experienced users in applied research are…