Interactive active learning for fairness with partial group label

Interactive active learning for fairness with partial group label

The rapid development of AI technologies has found numerous applications across various domains in human society. Ensuring fairness and preventing discrimination are critical considerations in the development of AI models. However, incomplete information often hinders the complete collection of sens...

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Bibliographic Details
Main Authors: Zeyu Yang, Jizhi Zhang, Fuli Feng, Chongming Gao, Qifan Wang, Xiangnan He
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2023-01-01
Series:AI Open
Subjects:
AI ethics
Trust
Fairness
Humans and AI
Active learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2666651023000190

Internet

http://www.sciencedirect.com/science/article/pii/S2666651023000190

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