Publications

Amir Jalilifard, Anderson De Rezende Rocha, M. M. Raimundo (2025). Reasoning Distillation and Structural Alignment for Improved Code Generation. arXiv.org.

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Tommaso Giovannelli, M. M. Raimundo, Luis Nunes Vicente (2025). Pareto sensitivity, most-changing sub-fronts, and knee solutions. Preprint.

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Sujoy Chatterjee, Everton Romanzini Colombo, M. M. Raimundo (2025). Multi-criteria Rank-based Aggregation for Explainable AI. IEEE International Joint Conference on Neural Network.

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J. S. B. Pereira, Giovani Valdrighi, M. M. Raimundo (2025). M²FGB: A Min-Max Gradient Boosting Framework for Subgroup Fairness. Conference on Fairness, Accountability and Transparency.

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M. M. Raimundo, Germain García-Zanabria, L. G. Nonato, Jorge Poco (2025). CounterCrime - Using Counterfactual Explanations to Explore Crime Reduction Scenarios. IEEE Transactions on Visualization and Computer Graphics.

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G. K. Bonás, Marcelo S. Reis, M. M. Raimundo (2025). Combinatorial U-Curve Optimization for Multi-Task Learning: A Task Selection Approach. IEEE International Joint Conference on Neural Network.

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Lucas Resck, M. M. Raimundo, Jorge Poco (2024). Exploring the Trade-off Between Model Performance and Explanation Plausibility of Text Classifiers Using Human Rationales. NAACL-HLT.

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Giovani Valdrighi, Athyrson M. Ribeiro, Jansen S. B. Pereira, Vitoria Guardieiro, Arthur Hendricks, Décio Miranda Filho, Juan David Nieto Garcia, Felipe F. Bocca, Thalita B. Veronese, Lucas Wanner, Marcos Medeiros Raimundo (2024). Best practices for responsible machine learning in credit scoring. Neural computing & applications (Print).

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Vitória Guardieiro, M. M. Raimundo, Jorge Poco (2023). Enforcing fairness using ensemble of diverse Pareto-optimal models. Data mining and knowledge discovery.

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Vitória Guardieiro, M. M. Raimundo, Jorge Poco (2022). Analyzing the Equity of the Brazilian National High School Exam by Validating the Item Response Theory's Invariance. Educational Data Mining.

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I. D. Computação, G. K. Bonás, Marcelo Da, Silva Reis, Marcos Medeiros, Giovana Kerche Bon´as, Marcelo S. Reis, M. M. Raimundo (2022). An algorithm for multi-task learning based on combinatorial optimization of U-curves. Preprint.

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M. M. Raimundo, L. G. Nonato, Jorge Poco (2021). Mining Pareto-optimal counterfactual antecedents with a branch-and-bound model-agnostic algorithm. Data mining and knowledge discovery.

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M. M. Raimundo, Thalita F. Drumond, A. C. R. Marques, Christiano Lyra, A. Rocha, F. J. Zuben (2021). Exploring multiobjective training in multiclass classification. Neurocomputing.

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Germain García-Zanabria, M. M. Raimundo, Jorge Poco, M. Nery, Cláudio T. Silva, S. Adorno, L. G. Nonato (2021). CriPAV: Street-Level Crime Patterns Analysis and Visualization. IEEE Transactions on Visualization and Computer Graphics.

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M. M. Raimundo, F. J. Zuben (2020). Multi-criteria analysis involving Pareto-optimal misclassification tradeoffs on imbalanced datasets. IEEE International Joint Conference on Neural Network.

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M. M. Raimundo, F. J. Zuben (2018). Investigating multiobjective methods in multitask classification. IEEE International Joint Conference on Neural Network.

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A. C. R. Marques, Marcos M Raimundo, Ellen Marianne B Cavalheiro, Luis F P Salles, Christiano Lyra, Fernando J Von Zuben (2018). Ant genera identification using an ensemble of convolutional neural networks. PLoS ONE.

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M. M. Raimundo, F. J. Zuben (2017). Many-Objective Ensemble-Based Multilabel Classification. Iberoamerican Congress on Pattern Recognition.

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F. S. Beserra, M. M. Raimundo, F. J. Zuben (2017). Ensembles of Multiobjective-Based Classifiers for Detection of Epileptic Seizures. Iberoamerican Congress on Pattern Recognition.

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M. M. Raimundo, P. Ferreira, F. J. Zuben (2017). An extension of the non-inferior set estimation algorithm for many objectives. European Journal of Operational Research.

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