30 citations · 56 across the 14 of their papers we have counts for
5 papers · 1 filter
Multicriteria decision support employing adaptive prediction in a tensor-based feature representation
Betania Silva Carneiro Campello, Leonardo Tomazeli Duarte, João Marcos Travassos Romano
Multicriteria decision analysis (MCDA) is a widely used tool to support decisions in which a set of alternatives should be ranked or classified based on multiple criteria. Recent s…
A statistical approach to detect sensitive features in a group fairness setting
Guilherme Dean Pelegrina, Miguel Couceiro, Leonardo Tomazeli Duarte
The use of machine learning models in decision support systems with high societal impact raised concerns about unfair (disparate) results for different groups of people. When evalu…
A -additive Choquet integral-based approach to approximate the SHAP values for local interpretability in machine learning
Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, Michel Grabisch
Besides accuracy, recent studies on machine learning models have been addressing the question on how the obtained results can be interpreted. Indeed, while complex machine learning…
A novel approach for Fair Principal Component Analysis based on eigendecomposition
Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte
Principal component analysis (PCA), a ubiquitous dimensionality reduction technique in signal processing, searches for a projection matrix that minimizes the mean squared error bet…
Analysis of Trade-offs in Fair Principal Component Analysis Based on Multi-objective Optimization
Guilherme D. Pelegrina, Renan D. B. Brotto, Leonardo T. Duarte +2
In dimensionality reduction problems, the adopted technique may produce disparities between the representation errors of different groups. For instance, in the projected space, a s…