30 citations · 55 across the 14 of their papers we have counts for
14 papers
A fairness-aware extension of Stochastic Multicriteria Acceptability Analysis for ranking
Guilherme Dean Pelegrina, Renata Pelissari
Fairness has become a central concern in ranking problems involving individuals or social groups, particularly under the Responsible Artificial Intelligence agenda. In Multi-Criter…
Shapley Regression for Rare Disease Diagnosis Support: a case study on APDS
Safa Alsaidi, Tomás Brogueira, Nizar Mahlaoui +5
Activated PI3K8 Syndrome (APDS) is a rare genetic immune disorder caused by variants in PIK3CD or PIK3R1, with highly heterogeneous symptoms that often delay diagnosis. Early recog…
Shapley Value Approximation Based on k-Additive Games
Guilherme Dean Pelegrina, Patrick Kolpaczki, Eyke Hüllermeier
The Shapley value is the prevalent solution for fair division problems in which a payout is to be divided among multiple agents. By adopting a game-theoretic view, the idea of fair…
Mitigating subjectivity and bias in AI development indices: A robust approach to redefining country rankings
Betania Silva C Campello, Guilherme Dean Pelegrina, Renata Pelissari +2
Countries worldwide have been implementing different actions national strategies for Artificial Intelligence (AI) to shape policy priorities and guide their development concerning…
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…
Shapley value-based approaches to explain the robustness of classifiers in machine learning
Guilherme Dean Pelegrina, Sajid Siraj
The use of algorithm-agnostic approaches is an emerging area of research for explaining the contribution of individual features towards the predicted outcome. Whilst there is a foc…
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…
An unsupervised capacity identification approach based on Sobol' indices
Guilherme D. Pelegrina, Leonardo T. Duarte, Michel Grabisch +1
In many ranking problems, some particular aspects of the addressed situation should be taken into account in the aggregation process. An example is the presence of correlations bet…
Muticriteria decision making based on independent component analysis: A preliminary investigation considering the TOPSIS approach
Guilherme D. Pelegrina, Leonardo T. Duarte, João M. T. Romano
This work proposes the application of independent component analysis to the problem of ranking different alternatives by considering criteria that are not necessarily statistically…
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…
Application of independent component analysis and TOPSIS to deal with dependent criteria in multicriteria decision problems
Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, João Marcos Travassos Romano
A vast number of multicriteria decision making methods have been developed to deal with the problem of ranking a set of alternatives evaluated in a multicriteria fashion. Very ofte…
Application of multi-objective optimization to blind source separation
Guilherme Dean Pelegrina, Romis Attux, Leonardo Tomazeli Duarte
Several problems in signal processing are addressed by expert systems which take into account a set of priors on the sought signals and systems. For instance, blind source separati…
A Multi-Objective Approach for Post-Nonlinear Source Separation and its Application to Ion-Selective Electrodes
Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte
Blind source separation (BSS) methods have been applied to deal with the lack of selectivity of ion-selective electrodes (ISE). In this paper, differently from the standard BSS sol…