VOGA: Variable Ordering Genetic Algorithm for Learning Bayesian Classifiers. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr. (HIS, 2006)

Conditional independence based learning of bayesian classifiers guided by a variable ordering genetic search. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti (IEEE Congress on Evolutionary Computation, 2007)

Feature-weighted k-Nearest Neighbor Classifier. - Diego P. Vivencio; Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti; Edimilson Batista dos Santos; Sebastian D. C. de O. Galvão (FOCI, 2007)

Variable Ordering in the Conditional Independence Bayesian Classifier Induction Process: An Evolutionary Approach. - Estevam R. Hruschka Jr.; Edimilson Batista dos Santos; Sebastian D. C. de O. Galvão (HIS, 2007)

A Distance-Based Mutation Operator for learning Bayesian Network structures using Evolutionary Algorithms. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr.; Eduardo R. Hruschka; Nelson F. F. Ebecken (IEEE Congress on Evolutionary Computation, 2010)

Evolutionary Algorithm Using Random Multi-point Crossover Operator for Learning Bayesian Network Structures. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr.; Nelson F. F. Ebecken (ICMLA, 2010)

Learning Bayesian Network structures using Multiple Offspring Sampling. - Edimilson Batista dos Santos; Nelson F. F. Ebecken; Estevam R. Hruschka Jr. (ISDA, 2011)

Bayesian network classifiers: Beyond classification accuracy. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr.; Eduardo R. Hruschka; Nelson F. F. Ebecken (Intell. Data Anal., 2011)

Bayesian networks for obstacle classification in agricultural environments. - Edimilson Batista dos Santos; Caio César Teodoro Mendes; Fernando Santos Osório; Denis Fernando Wolf (ITSC, 2013)

The influences of canonical evolutionary algorithm operators and variable orderings in learning Bayesian classifiers from data. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti; Nelson F. F. Ebecken (Int. J. Hybrid Intell. Syst., 2014)

Bayesian Networks for Identifying Semantic Relations in a Never-Ending Learning System. - Edimilson Batista dos Santos; Massilon Lourenço Fernandes; Estevam R. Hruschka Jr.; Maísa Cristina Duarte (ISDA, 2016)

Bayesian Networks for Inference and Discovery of Semantic Relations in a Never-Ending Learning System. - Edimilson Batista dos Santos; Igor Henrique P. Rodrigues; Estevam R. Hruschka Jr.; Lucas Rezende Bruno (BRACIS, 2019)

Predicting the Disease Outcome in COVID-19 Positive Patients Through Machine Learning: A Retrospective Cohort Study With Brazilian Data. - Fernanda Sumika Hojo de Souza; Natália Satchiko Hojo-Souza; Edimilson Batista dos Santos; Cristiano Maciel da Silva; Daniel Ludovico Guidoni (Frontiers Artif. Intell., 2021)

Improving the FQF Distributional Reinforcement Learning Algorithm in MinAtar Environment. - Júlio César Mendes de Resende; Edimilson Batista dos Santos; Marcos Antonio de Matos Laia (BRACIS (1), 2022)

Combining Improvements in FQF Distributional Reinforcement Learning Algorithm. - Júlio César Mendes de Resende; Edimilson Batista dos Santos; Marcos Antonio de Matos Laia (ICMLA, 2023)

Convolutional neural networks applied to data organized as OLAP cubes. - Rodrigo Ribeiro Caputo; Edimilson Batista dos Santos; Leonardo Chaves Dutra da Rocha (Expert Syst. J. Knowl. Eng., 2023)