Search Results for author:
Found 2 papers, 0 papers with code
Connecting Algorithmic Fairness to Quality Dimensions in Machine Learning in Official Statistics and Survey Production
We employ Yung et al. (2022)'s QF4SA quality framework and present a mapping of its quality dimensions to algorithmic fairness.
Sources of Uncertainty in Machine Learning -- A Statisticians' View
Machine Learning and Deep Learning have achieved an impressive standard today, enabling us to answer questions that were inconceivable a few years ago.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
