3 papers
stat.ML2025
Machine learning in an expectation-maximisation framework for nowcasting
Paul Wilsens, Katrien Antonio, Gerda Claeskens
Decision making often occurs in the presence of incomplete information, leading to the under- or overestimation of risk. Leveraging the observable information to learn the complete…
cs.LG2025
Machine Learning with Multitype Protected Attributes: Intersectional Fairness through Regularisation
Ho Ming Lee, Katrien Antonio, Benjamin Avanzi +2
Ensuring equitable treatment (fairness) across protected attributes (such as gender or ethnicity) is a critical issue in machine learning. Most existing literature focuses on binar…
stat.ME2024
Reducing the dimensionality and granularity in hierarchical categorical variables
Paul Wilsens, Katrien Antonio, Gerda Claeskens
Hierarchical categorical variables often exhibit many levels (high granularity) and many classes within each level (high dimensionality). This may cause overfitting and estimation…