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Fair Domain Generalization: An Information-Theoretic View
Tangzheng Lian, Guanyu Hu, Dimitrios Kollias, Xinyu Yang, Oya Celiktutan
https://arxiv.org/abs/2507.05823

Fair Domain Generalization: An Information-Theoretic View
Domain generalization (DG) and algorithmic fairness are two critical challenges in machine learning. However, most DG methods focus only on minimizing expected risk in the unseen target domain without considering algorithmic fairness. Conversely, fairness methods typically do not account for domain shifts, so the fairness achieved during training may not generalize to unseen test domains. In this work, we bridge these gaps by studying the problem of Fair Domain Generalization (FairDG), which ai…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[7/7]:
- From Data-Driven to Purpose-Driven Artificial Intelligence: Systems Thinking for Data-Analytic Au...
Anadria, Dobbe, Giachanou, Kuiper, Bartels, van Amsterdam, de Troya, Z\"urcher, Oberski
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