4 papers
Constructing Magic Squares: an integer constraint satisfaction problem and a fast approach
João Vitor Pamplona, Maria Eduarda Pinheiro, Luiz-Rafael Santos
Magic squares are a fascinating mathematical challenge that has intrigued mathematicians for centuries. Given a positive (and possibly large) integer \( n \), one of the main chall…
FairML: A Julia Package for Fair Classification
Jan Pablo Burgard, João Vitor Pamplona
In this paper, we propose FairML.jl, a Julia package providing a framework for fair classification in machine learning. In this framework, the fair learning process is divided into…
Fair Generalized Linear Mixed Models
Jan Pablo Burgard, João Vitor Pamplona
When using machine learning for automated prediction, it is important to account for fairness in the prediction. Fairness in machine learning aims to ensure that biases in the data…
Fair Mixed Effects Support Vector Machine
Jan Pablo Burgard, João Vitor Pamplona
To ensure unbiased and ethical automated predictions, fairness must be a core principle in machine learning applications. Fairness in machine learning aims to mitigate biases prese…