Variable Selection in the Context of AI Fairness

arXiv:2506.10586v2 Announce Type: replace-cross Abstract: Determining whether an algorithmic decision-making system discriminates against a specific demographic typically involves

arXiv:2604.07009v1 Announce Type: new Abstract: Ensuring fairness in machine learning predictions is a critical challenge, especially when models are deployed in sensitive domains

arXiv:2605.15295v1 Announce Type: cross Abstract: Machine learning (ML) algorithms are increasingly deployed in high-stakes decision-making domains such as loan approvals, hiring,

arXiv:2511.20909v2 Announce Type: replace-cross Abstract: Machine learning models trained on real-world data may inadvertently make biased predictions that negatively impact

arXiv:2604.21036v1 Announce Type: new Abstract: Text-to-image(T2I) models like Stable Diffusion and DALL-E have made generative AI widely accessible, yet recent studies reveal