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Conference Paper

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices

MPS-Authors
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Speicher,  Till
Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society;

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Grgić-Hlača,  Nina
Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society;

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Gummadi,  Krishna P.
Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society;

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Singla,  Adish
Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society;

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Zafar,  Muhammad Bilal
Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society;

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3219819.3220046.pdf
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Citation

Speicher, T., Heidari, H., Grgić-Hlača, N., Gummadi, K. P., Singla, A., Weller, A., et al. (2018). A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices. In KDD'18 (pp. 2239-2248). New York, NY: ACM. doi:10.1145/3219819.3220046.


Cite as: https://hdl.handle.net/21.11116/0000-0003-47C6-E
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