Data augmentation via diffusion model to enhance AI fairness
Experimental results demonstrate that the synthetic data generated by Tab-DDPM improves fairness in binary classification.
Authors
- Xishuang Dong (ORCID: https://orcid.org/0000-0002-3742-0071)
- Pamela Obiomon
- Lijun Qian (ORCID: https://orcid.org/0000-0003-1577-3359)
- Camille Gibson (ORCID: https://orcid.org/0000-0001-8409-5606)
- Christina Hastings Blow
Institutions
- Texas A&M University System (US)
- Prairie View A&M University (US)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2025-03-19
- DOI
- https://doi.org/10.3389/frai.2025.1530397
- Citations
- 3
- Primary Topic
- Machine Learning and Data Classification
- Type
- article
- Field-Weighted Citation Impact
- 7.44