Learning fair representations via an adversarial framework
Fairness has become a central issue for our research community as classification algorithms are adopted in societally critical domains such as recidivism prediction and loan approval. In this work, we consider the potential bias based on protected attributes (e.g., race and gender), and tackle this...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co. Ltd.
2023-01-01
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| Series: | AI Open |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666651023000050 |