26 citations · 50 across the 4 of their papers we have counts for
4 papers
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…
Evaluation of group fairness measures in student performance prediction problems
Tai Le Quy, Thi Huyen Nguyen, Gunnar Friege +1
Predicting students' academic performance is one of the key tasks of educational data mining (EDM). Traditionally, the high forecasting quality of such models was deemed critical.…
Multiple Fairness and Cardinality constraints for Students-Topics Grouping Problem
Tai Le Quy, Gunnar Friege, Eirini Ntoutsi
Group work is a prevalent activity in educational settings, where students are often divided into topic-specific groups based on their preferences. The grouping should reflect the…
Fair-Capacitated Clustering
Tai Le Quy, Arjun Roy, Gunnar Friege +1
Traditionally, clustering algorithms focus on partitioning the data into groups of similar instances. The similarity objective, however, is not sufficient in applications where a f…