1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
Towards Inferential Reproducibility of Machine Learning Research
Michael Hagmann, Philipp Meier, Stefan Riezler
Reliability of machine learning evaluation -- the consistency of observed evaluation scores across replicated model training runs -- is affected by several sources of nondeterminis…
cs.LG2022
Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis
Shigehiko Schamoni, Michael Hagmann, Stefan Riezler
Ensembling neural networks is a long-standing technique for improving the generalization error of neural networks by combining networks with orthogonal properties via a committee d…
cs.LG2021
False perfection in machine prediction: Detecting and assessing circularity problems in machine learning
Michael Hagmann, Stefan Riezler
This paper is an excerpt of an early version of Chapter 2 of the book "Validity, Reliability, and Significance. Empirical Methods for NLP and Data Science", by Stefan Riezler and M…