Bias mitigation for machine learning classifiers: A comprehensive survey
This article provides a comprehensive survey of bias mitigation methods for achieving
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …
BenchIMP: A benchmark for quantitative evaluation of the incident management process assessment
A Palma, N Bartoloni, M Angelini - Proceedings of the 19th International …, 2024 - dl.acm.org
In the current scenario, where cyber-incidents occur daily, an effective Incident Management
Process (IMP) and its assessment have assumed paramount significance. While …
Process (IMP) and its assessment have assumed paramount significance. While …
ProxiMix: Enhancing Fairness with Proximity Samples in Subgroups
Many bias mitigation methods have been developed for addressing fairness issues in
machine learning. We found that using linear mixup alone, a data augmentation technique …
machine learning. We found that using linear mixup alone, a data augmentation technique …