4 papers
Affinity Clustering Framework for Data Debiasing Using Pairwise Distribution Discrepancy
Siamak Ghodsi, Eirini Ntoutsi
Group imbalance, resulting from inadequate or unrepresentative data collection methods, is a primary cause of representation bias in datasets. Representation bias can exist with re…
Multi-dimensional discrimination in Law and Machine Learning -- A comparative overview
Arjun Roy, Jan Horstmann, Eirini Ntoutsi
AI-driven decision-making can lead to discrimination against certain individuals or social groups based on protected characteristics/attributes such as race, gender, or age. The do…
Explaining text classifiers through progressive neighborhood approximation with realistic samples
Yi Cai, Arthur Zimek, Eirini Ntoutsi +1
The importance of neighborhood construction in local explanation methods has been already highlighted in the literature. And several attempts have been made to improve neighborhood…
A review of clustering models in educational data science towards fairness-aware learning
Tai Le Quy, Gunnar Friege, Eirini Ntoutsi
Ensuring fairness is essential for every education system. Machine learning is increasingly supporting the education system and educational data science (EDS) domain, from decision…