2 papers
cs.LG2024
Fair-OBNC: Correcting Label Noise for Fairer Datasets
Inês Oliveira e Silva, Sérgio Jesus, Hugo Ferreira +4
Data used by automated decision-making systems, such as Machine Learning models, often reflects discriminatory behavior that occurred in the past. These biases in the training data…
cs.LG2023
Systematic analysis of the impact of label noise correction on ML Fairness
I. Oliveira e Silva, C. Soares, I. Sousa +1
Arbitrary, inconsistent, or faulty decision-making raises serious concerns, and preventing unfair models is an increasingly important challenge in Machine Learning. Data often refl…