Guilherme Dean Pelegrina

According to our database, Guilherme Dean Pelegrina authored at least 19 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Novel Approach for Fair Principal Component Analysis Based on Eigendecomposition.

Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte

IEEE Trans. Artif. Intell., March, 2024

Mitigating subjectivity and bias in AI development indices: A robust approach to redefining country rankings.

Betania Silva Carneiro Campello, Guilherme Dean Pelegrina, Renata Pelissari, Ricardo Suyama, Leonardo Tomazeli Duarte

CoRR, 2024

2023

A <i>k</i>-additive Choquet integral-based approach to approximate the SHAP values for local interpretability in machine learning.

Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, Michel Grabisch

Artif. Intell., December, 2023

Interpreting the Contribution of Sensors in Blind Source Extraction by Means of Shapley Values.

Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, Michel Grabisch

IEEE Signal Process. Lett., 2023

A statistical approach to detect sensitive features in a group fairness setting.

Guilherme Dean Pelegrina, Miguel Couceiro, Leonardo Tomazeli Duarte

CoRR, 2023

Critical Analysis of AI Indicators in Terms of Weighting and Aggregation Approaches.

Renata Pelissari, Betania Silva Carneiro Campello, Guilherme Dean Pelegrina, Ricardo Suyama, Leonardo Tomazeli Duarte

Proceedings of the Intelligent Systems - 12th Brazilian Conference, 2023

2022

A k-additive Choquet integral-based approach to approximate the SHAP values for local interpretability in machine learning.

Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, Michel Grabisch

CoRR, 2022

Shapley value-based approaches to explain the robustness of classifiers in machine learning.

Guilherme Dean Pelegrina, Sajid Siraj

CoRR, 2022

Dealing with redundancies among criteria in multicriteria decision making through independent component analysis.

Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, Michel Grabisch, João Marcos Travassos Romano

Comput. Ind. Eng., 2022

Analysis of Trade-offs in Fair Principal Component Analysis Based on Multi-objective Optimization.

Guilherme Dean Pelegrina, Renan D. B. Brotto, Leonardo Tomazeli Duarte, Romis Attux, João M. T. Romano

Proceedings of the International Joint Conference on Neural Networks, 2022

2020

The multilinear model in multicriteria decision making: The case of 2-additive capacities and contributions to parameter identification.

Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, Michel Grabisch, João Marcos Travassos Romano

Eur. J. Oper. Res., 2020

A multi-objective-based approach for Fair Principal Component Analysis.

Guilherme Dean Pelegrina, Renan D. B. Brotto, Leonardo Tomazeli Duarte, João M. T. Romano, Romis Attux

CoRR, 2020

An Unsupervised Capacity Identification Approach Based on Sobol' Indices.

Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, Michel Grabisch, João Marcos Travassos Romano

Proceedings of the Modeling Decisions for Artificial Intelligence, 2020

2019

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

Expert Syst. Appl., 2019

Application of multi-objective optimization to blind source separation.

Guilherme Dean Pelegrina, Romis Attux, Leonardo Tomazeli Duarte

Expert Syst. Appl., 2019

2018

A Multi-Objective Approach for Post-Nonlinear Source Separation and Its Application to Ion-Selective Electrodes.

Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte

IEEE Trans. Circuits Syst. II Express Briefs, 2018

Muticriteria Decision Making Based on Independent Component Analysis: A Preliminary Investigation Considering the TOPSIS Approach.

Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, João Marcos Travassos Romano

Proceedings of the Latent Variable Analysis and Signal Separation, 2018

2016

Blind source separation and feature extraction in concurrent control charts pattern recognition: Novel analyses and a comparison of different methods.

Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte, Christian Jutten

Comput. Ind. Eng., 2016

A multi-objective approach for blind source extraction.

Guilherme Dean Pelegrina, Leonardo Tomazeli Duarte

Proceedings of the 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016