2019
- RBC Prudêncio. Cost Sensitive Evaluation of Instance Hardness in Machine Learning. European Conference on Machine Learning 2019.
- F Martınez-Plumed, RBC Prudêncio, A Martınez-Usó, J Hernández-Orallo. Item response theory in AI: Analysing machine learning classifiers at the instance level. Artificial Intelligence 271, 18-42.
- Yu Chen, Telmo Silva Filho, Ricardo B. C. Prudêncio, Tom Diethe, Peter Flach. β3-IRT: A New Item Response Model and its Applications. 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019).
- D Pereira-Santos, RBC Prudêncio, AC de Carvalho. Empirical investigation of active learning strategies. Neurocomputing. 326, 15-27.
2018
- AC Lorena, AI Maciel, PBC de Miranda, IG Costa, RBC Prudêncio . Data complexity meta-features for regression problems. Machine Learning 107 (1), 209-246
- JEA Gomes, RBC Prudêncio, ACA Nascimento. Centrality-Based Group Profiling: A Comparative Study in Co-authorship Networks. New Generation Computing 36 (1), 59-89
- PBC Miranda, RBC Prudêncio. A novel context-free grammar for the generation of PSO algorithms. Natural Computing, 1-19
- M Wanderley , RBC Prudêncio. Transferring Knowledge From Texts to Images by Combining Deep Semantic Feature Descriptors. 2018 International Joint Conference on Neural Networks (IJCNN)
2017
2016
- ACA Nascimento, RBC Prudêncio, IG Costa. A multiple kernel learning algorithm for drug-target interaction prediction. BMC bioinformatics 17 (1), 46
- TM Silva Filho, RMCR Souza, RBC Prudêncio. A swarm-trained k-nearest prototypes adaptive classifier with automatic feature selection for interval data. Neural Networks 80, 19-33
- AFM Sousa, RBC Prudêncio, TB Ludermir, C Soares. Active learning and data manipulation techniques for generating training examples in meta-learning. Neurocomputing 194, 45-55
- F Martınez-Plumed, RBC Prudêncio, A Martınez-Usó, J Hernández-Orallo. Making sense of item response theory in machine learning. Proceedings of 22nd European Conference on Artificial Intelligence (Best Paper Award)
- J Hernández-Orallo, A Martínez-Usó, RBC Prudêncio, M Kull, P Flach, ... Reframing in context: A systematic approach for model reuse in machine learning. AI Communications 29 (5), 551-566