7 citations · 12 across the 2 of their papers we have counts for
2 papers
cs.CV2022★ 7 cited
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers
Dominik Zietlow, Michael Lohaus, Guha Balakrishnan +4
Algorithmic fairness is frequently motivated in terms of a trade-off in which overall performance is decreased so as to improve performance on disadvantaged groups where the algori…
cs.LG2019★ 5 cited
Uncertainty Estimates for Ordinal Embeddings
Michael Lohaus, Philipp Hennig, Ulrike von Luxburg
To investigate objects without a describable notion of distance, one can gather ordinal information by asking triplet comparisons of the form "Is object closer to or is …