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researcher

Michael Lohaus

4 papers hereh-index 5213 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.CV1

identity via Semantic Scholar / OpenAlex

most citedLeveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers

7 citations · 17 across the 4 of their papers we have counts for

collaborators
Showing cs.LGShow all

3 papers · 1 filter

cs.LG2022★ 4 cited

Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks

Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi +2

We show that deep networks trained to satisfy demographic parity often do so through a form of race or gender awareness, and that the more we force a network to be fair, the more a…

cs.LG2019★ 1 cited

Insights into Ordinal Embedding Algorithms: A Systematic Evaluation

Leena Chennuru Vankadara, Siavash Haghiri, Michael Lohaus +2

The objective of ordinal embedding is to find a Euclidean representation of a set of abstract items, using only answers to triplet comparisons of the form "Is item i closer to th…

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 x closer to y or is x…

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