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Michael Lohaus
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2020 – today
- 2023
- [j1]Leena Chennuru Vankadara, Michael Lohaus, Siavash Haghiri, Faiz Ul Wahab, Ulrike von Luxburg:
Insights into Ordinal Embedding Algorithms: A Systematic Evaluation. J. Mach. Learn. Res. 24: 191:1-191:83 (2023) - 2022
- [b1]Michael Lohaus:
Limitations of Fairness in Machine Learning. Tübingen University, Germany, 2022 - [c3]Dominik Zietlow, Michael Lohaus, Guha Balakrishnan, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Chris Russell
:
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. CVPR 2022: 10400-10411 - [c2]Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell:
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. NeurIPS 2022 - [i3]Dominik Zietlow, Michael Lohaus, Guha Balakrishnan
Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers. CoRR abs/2203.04913 (2022) - [i2]Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. CoRR abs/2204.04440 (2022) - 2020
- [c1]Michael Lohaus, Michaël Perrot, Ulrike von Luxburg:
Too Relaxed to Be Fair. ICML 2020: 6360-6369
2010 – 2019
- 2019
- [i1]Michael Lohaus, Philipp Hennig, Ulrike von Luxburg:
Uncertainty Estimates for Ordinal Embeddings. CoRR abs/1906.11655 (2019)
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