1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2025★ 1 cited
A Multi-Objective Evaluation Framework for Analyzing Utility-Fairness Trade-Offs in Machine Learning Systems
Gökhan Özbulak, Oscar Jimenez-del-Toro, Maíra Fatoretto +2
The evaluation of fairness models in Machine Learning involves complex challenges, such as defining appropriate metrics, balancing trade-offs between utility and fairness, and ther…
cs.CV2024
Does Data-Efficient Generalization Exacerbate Bias in Foundation Models?
Dilermando Queiroz, Anderson Carlos, Maíra Fatoretto +3
Foundation models have emerged as robust models with label efficiency in diverse domains. In medical imaging, these models contribute to the advancement of medical diagnoses due to…