| 2022 | ICPR | Kolmogorov-Smirnov and ROC curve metrics for binary classification performance assessment are equivalent. | Paulo J. L. Adeodato, Slvio B. Melo |
| 2022 | IJCNN | A geometric proof of the equivalence between AUC_ROC and Gini index area metrics for binary classifier performance assessment. | Paulo J. L. Adeodato, Slvio B. Melo |
| 2020 | EDM | Where to aim? Factors that influence the performance of Brazilian secondary schools. | Paulo J. L. Adeodato, Rogerio Luiz C. S. Filho |
| 2016 | IJCNN | Polynomial approximation RAM neuron capable of handling true continuous input variables. | Paulo J. L. Adeodato, Rosalvo F. Oliveira Neto |
| 2015 | IDEAL | Variable Transformation for Granularity Change in Hierarchical Databases in Actual Data Mining Solutions. | Paulo J. L. Adeodato |
| 2014 | IJCNN | Continuous variables segmentation and reordering for optimal performance on binary classification tasks. | Paulo J. L. Adeodato, Domingos S. P. Salazar, Lucas S. Gallindo, Abner G. Sa, Starch Melo de Souza |
| 2014 | SEKE | CoMoVi: a Framework for Data Transformation in Credit Behavioral Scoring Applications Using Model Driven Architecture. | Rosalvo F. O. Neto, Paulo J. L. Adeodato, Ana Carolina Salgado, Dailton Rodrigues de Carvalho Filho, Genival Rocha Machado |
| 2013 | CBMS | Evaluation of the use of computational intelligence techniques in medical claim processes of a health insurance company. | Flvio H. D. Arajo, Lailson B. Moraes, Andr M. Santana, Pedro de A. Santos Neto, Paulo J. L. Adeodato, rico Leo |
| 2013 | ICMLA | A Temporal Difference GNG-Based Algorithm That Can Learn to Control in Reinforcement Learning Environments. | Davi C. de L. Vieira, Paulo J. L. Adeodato, Paulo M. Goncalves Junior |
| 2011 | IJCNN | PCA and Gaussian noise in MLP neural network training improve generalization in problems with small and unbalanced data sets. | Icamaan B. Viegas da Silva, Paulo J. L. Adeodato |
| 2011 | SMC | Predicting software defects: A cost-sensitive approach. | Miguel E. R. Bezerra, Adriano L. I. Oliveira, Paulo J. L. Adeodato |
| 2010 | IJCNN | pRAM n-tuple Classifier - a new architecture of probabilistic RAM neurons for classification problems. | Paulo J. L. Adeodato, Rosalvo F. O. Neto |
| 2010 | SMC | Improving reinforcement learning algorithms by the use of data mining techniques for feature and action selection. | Davi C. de L. Vieira, Paulo J. L. Adeodato, Paulo M. Goncalves |
| 2009 | IJCNN | The role of temporal feature extraction and bagging of MLP neural networks for solving the WCCI 2008 Ford Classification Challenge. | Paulo J. L. Adeodato, Adrian L. Arnaud, Germano C. Vasconcelos, Rodrigo C. L. V. Cunha, Tarcsio B. Gurgel, Domingos S. M. P. Monteiro |
| 2009 | IJCNN | A data mining approach to solve the goal scoring problem. | Renato Oliveira, Paulo J. L. Adeodato, Arthur Carvalho, Icamaan Viegas, Christian Diego, Ing Ren Tsang |
| 2009 | IRI | Integration and Knowledge Reuse Environment for Producing Award Winning Solutions for Binary Decision Data Mining Problems. | Rodrigo C. L. V. Cunha, Paulo J. L. Adeodato, Silvio R. L. Meira |
| 2008 | ICPR | A systematic solution for the NN3 Forecasting Competition problem based on an ensemble of MLP neural networks. | Paulo J. L. Adeodato, Germano C. Vasconcelos, Adrian L. Arnaud, Rodrigo C. L. V. Cunha, Domingos Svio Malaquias Pessoa Monteiro |
| 2007 | CIDM | A New Evolutionary Approach for Time Series Forecasting. | Tiago A. E. Ferreira, Germano C. Vasconcelos, Paulo J. L. Adeodato |
| 2005 | GECCO | A new evolutionary method for time series forecasting. | Tiago A. E. Ferreira, Germano C. Vasconcelos, Paulo J. L. Adeodato |
| 2004 | CEC | A hybrid intelligent system approach for improving the prediction of real world time series. | Tiago A. E. Ferreira, Germano C. Vasconcelos, Paulo J. L. Adeodato |
| 2004 | ICPR | Neural Networks vs Logistic Regression: a Comparative Study on a Large Data Set. | Paulo J. L. Adeodato, Germano C. Vasconcelos, Adrian L. Arnaud, Roberto A. F. Santos, Rodrigo C. L. V. Cunha, Domingos S. M. P. Monteiro |
| 1996 | ICANN | Autoassociative Memory with high Storage Capacity. | Paulo J. L. Adeodato, John G. Taylor |