Fair representation learning (FRL) is a popular class of methods aiming to produce fair
classifiers via data preprocessing. Recent regulatory directives stress the need for FRL …

Cargo ships navigating global waters are required to be sufficiently safe and compliant with
international treaties. Governmental inspectorates currently assess in a rule-based manner …

With the rise of artificial intelligence in our everyday lives, the need for human interpretation
of machine learning models' predictions emerges as a critical issue. Generally …

Decision trees are powerful tools for classification and regression that attract many
researchers working in the burgeoning area of machine learning. A decision tree has two …

Fair representation learning (FRL) is a popular class of methods aiming to produce fair
classifiers via data preprocessing. However, recent work has shown that prior methods …

Abstract Machine learning systems are widely used in daily lives, naturally making fairness
an important concern when designing and deploying these systems. Most bias mitigation …

This thesis focuses on bridging the overlap between the fields of Operations Research and
Machine Learning. We do so by providing efficient Mixed Integer Linear Optimization (MILO) …

This thesis is part of an extensive collaboration between the Dutch Ministry of Infrastructure
and Water Management (I&W) and Leiden University. My first personal encounter with I&W …

Abstract Machine learning algorithms have made their way into critical decision-making
processes. However, concerns have arisen regarding the bias that these algorithms can …