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Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning


Sep 09, 2021
Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum

* To appear in the 21st IEEE International Conference on Data Mining (ICDM 2021), Auckland, New Zealand 

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Accounting for Model Uncertainty in Algorithmic Discrimination


May 10, 2021
Junaid Ali, Preethi Lahoti, Krishna P. Gummadi

* 12 pages, Accepted at AIES 2021 

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Fairness without Demographics through Adversarially Reweighted Learning


Jun 24, 2020
Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi


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An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision


Oct 31, 2019
Hanchen Wang, Nina Grgic-Hlaca, Preethi Lahoti, Krishna P. Gummadi, Adrian Weller

* Accepted at NeurIPS 2019 HCML Workshop 

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Operationalizing Individual Fairness with Pairwise Fair Representations


Jul 02, 2019
Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum


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iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making


Jun 04, 2018
Preethi Lahoti, Gerhard Weikum, Krishna P. Gummadi


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