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ORCIDKweku Kwegyir-Aggrey
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2020 – today
- 2024
[i5]Kweku Kwegyir-Aggrey, Naveen Durvasula, Jennifer Wang, Suresh Venkatasubramanian:
Observing Context Improves Disparity Estimation when Race is Unobserved. CoRR abs/2409.01984 (2024)- 2023
- [c2]Kweku Kwegyir-Aggrey
, Marissa Gerchick, Malika Mohan, Aaron Horowitz, Suresh Venkatasubramanian:
The Misuse of AUC: What High Impact Risk Assessment Gets Wrong. FAccT 2023: 1570-1583 - [i4]Kweku Kwegyir-Aggrey, Marissa Gerchick, Malika Mohan, Aaron Horowitz, Suresh Venkatasubramanian:
The Misuse of AUC: What High Impact Risk Assessment Gets Wrong. CoRR abs/2305.18159 (2023) - 2022
- [i3]Kweku Kwegyir-Aggrey, Jessica Dai, John P. Dickerson, Keegan Hines:
Achieving Downstream Fairness with Geometric Repair. CoRR abs/2203.07490 (2022) - 2021
- [c1]Jessica Schrouff, Awa Dieng, Miriam Rateike, Kweku Kwegyir-Aggrey, Golnoosh Farnadi:
Algorithmic Fairness through the Lens of Causality and Robustness (AFCR) 2021. AFCR 2021: 1-5 - [e1]Jessica Schrouff, Awa Dieng, Miriam Rateike, Kweku Kwegyir-Aggrey, Golnoosh Farnadi:
Algorithmic Fairness through the Lens of Causality and Robustness Workshop, AFCR 2021, virtual, December 13, 2021. Proceedings of Machine Learning Research 171, PMLR 2021 [contents] - [i2]Kweku Kwegyir-Aggrey, Rebecca Santorella, Sarah M. Brown:
Everything is Relative: Understanding Fairness with Optimal Transport. CoRR abs/2102.10349 (2021) - [i1]Jessica Zosa Forde, A. Feder Cooper, Kweku Kwegyir-Aggrey, Chris De Sa, Michael Littman:
Model Selection's Disparate Impact in Real-World Deep Learning Applications. CoRR abs/2104.00606 (2021)
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