90 citations · 133 across the 7 of their papers we have counts for
5 papers · 1 filter
FairGBM: Gradient Boosting with Fairness Constraints
André F Cruz, Catarina Belém, Sérgio Jesus +3
Tabular data is prevalent in many high-stakes domains, such as financial services or public policy. Gradient Boosted Decision Trees (GBDT) are popular in these settings due to thei…
Weakly Supervised Multi-task Learning for Concept-based Explainability
Catarina Belém, Vladimir Balayan, Pedro Saleiro +1
In ML-aided decision-making tasks, such as fraud detection or medical diagnosis, the human-in-the-loop, usually a domain-expert without technical ML knowledge, prefers high-level c…
Promoting Fairness through Hyperparameter Optimization
André F. Cruz, Pedro Saleiro, Catarina Belém +2
Considerable research effort has been guided towards algorithmic fairness but real-world adoption of bias reduction techniques is still scarce. Existing methods are either metric-…
Teaching the Machine to Explain Itself using Domain Knowledge
Vladimir Balayan, Pedro Saleiro, Catarina Belém +2
Machine Learning (ML) has been increasingly used to aid humans to make better and faster decisions. However, non-technical humans-in-the-loop struggle to comprehend the rationale b…
A Bandit-Based Algorithm for Fairness-Aware Hyperparameter Optimization
André F. Cruz, Pedro Saleiro, Catarina Belém +2
Considerable research effort has been guided towards algorithmic fairness but there is still no major breakthrough. In practice, an exhaustive search over all possible techniques a…