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2020 – today
- 2024
[i6]Mercy Nyamewaa Asiedu, Awa Dieng, Iskandar Haykel, Negar Rostamzadeh, Stephen Pfohl, Chirag Nagpal, Maria Nagawa, Abigail Oppong, Sanmi Koyejo, Katherine A. Heller:
The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa. CoRR abs/2403.03357 (2024)- [i5]Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres, Darlene Neal, Mercy Nyamewaa Asiedu, Awa Dieng, Nenad Tomasev, Qazi Mamunur Rashid, Shekoofeh Azizi, Negar Rostamzadeh, Liam G. McCoy, Leo Anthony Celi, Yun Liu, Mike Schaekermann, Alanna Walton, Alicia Parrish, Chirag Nagpal, Preeti Singh, Akeiylah Dewitt, Philip Andrew Mansfield, Sushant Prakash, Katherine A. Heller, Alan Karthikesalingam, Christopher Semturs, Joelle K. Barral, Greg Corrado, Yossi Matias, Jamila Smith-Loud, Ivor Horn, Karan Singhal:
A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models. CoRR abs/2403.12025 (2024) - [i4]Mercy Nyamewaa Asiedu, Nenad Tomasev, Chintan Ghate, Tiya Tiyasirichokchai, Awa Dieng, Oluwatosin Akande, Geoffrey Siwo, Steve Adudans, Sylvanus Aitkins, Odianosen Ehiakhamen, Eric Ndombi, Katherine Heller:
Contextual Evaluation of Large Language Models for Classifying Tropical and Infectious Diseases. CoRR abs/2409.09201 (2024) - 2023
- [i3]Mercy Nyamewaa Asiedu, Awa Dieng, Abigail Oppong, Maria Nagawa, Sanmi Koyejo, Katherine A. Heller:
Globalizing Fairness Attributes in Machine Learning: A Case Study on Health in Africa. CoRR abs/2304.02190 (2023) - 2022
- [c4]Awa Dieng, Miriam Rateike, Golnoosh Farnadi, Ferdinando Fioretto, Matt J. Kusner, Jessica Schrouff:
Algorithmic Fairness through the Lens of Causality and Privacy (AFCP) 2022. AFCP 2022: 1-6 - [c3]Jessica Schrouff, Natalie Harris, Sanmi Koyejo, Ibrahim M. Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour:
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings. NeurIPS 2022 - [e2]Awa Dieng, Miriam Rateike, Golnoosh Farnadi, Ferdinando Fioretto, Matt J. Kusner, Jessica Schrouff:
Algorithmic Fairness through the Lens of Causality and Privacy Workshop, AFCP 2022, New Orleans, LA, USA (hybrid), 03 December 2022. Proceedings of Machine Learning Research 214, PMLR 2022 [contents] - [i2]Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour:
Maintaining fairness across distribution shift: do we have viable solutions for real-world applications? CoRR abs/2202.01034 (2022) - 2021
- [c2]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]
2010 – 2019
- 2019
- [c1]Awa Dieng, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky:
Interpretable Almost-Exact Matching for Causal Inference. AISTATS 2019: 2445-2453 - 2018
- [i1]Awa Dieng, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky:
Collapsing-Fast-Large-Almost-Matching-Exactly: A Matching Method for Causal Inference. CoRR abs/1806.06802 (2018)
Coauthor Index
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last updated on 2024-10-13 18:01 CEST by the dblp team
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