João Roberto Bertini Jr.

Affiliations:
  • Universidade Estadual de Campinas
  • Universidade de São Paulo


According to our database1, João Roberto Bertini Jr. authored at least 37 papers between 2006 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2020
Graph embedded rules for explainable predictions in data streams.
Neural Networks, 2020

Dynamic ensemble mechanisms to improve particulate matter forecasting.
Appl. Soft Comput., 2020

2019
An iterative boosting-based ensemble for streaming data classification.
Inf. Fusion, 2019

A comparison of machine learning algorithms as surrogate model for net present value prediction from wells arrangement data.
Proceedings of the International Joint Conference on Neural Networks, 2019

A Discretization-based Ensemble Learning Method for Classification in High-Speed Data Streams.
Proceedings of the International Joint Conference on Neural Networks, 2019

2018
Attribute-Based Decision Graphs and Their Roles in Machine Learning Related Tasks.
Proceedings of the Advances in Feature Selection for Data and Pattern Recognition, 2018

Approaching miRNA Family Classification Through Constructive Neural Networks.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017
Enhancing classification performance using attribute-oriented functionally expanded data.
Pattern Recognit. Lett., 2017

Attribute-based Decision Graphs: A framework for multiclass data classification.
Neural Networks, 2017

A methodology for enhancing data quality for classification purposes using attribute-based decision graphs.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2017

Online Sequential Learning Based on Extreme Learning Machines for Particulate Matter Forecasting.
Proceedings of the 2017 Brazilian Conference on Intelligent Systems, 2017

2016
Enhancing Constructive Neural Network Performance Using Functionally Expanded Input Data.
J. Artif. Intell. Soft Comput. Res., 2016

An embedded imputation method via Attribute-based Decision Graphs.
Expert Syst. Appl., 2016

Functionally expanded streaming data as input to classification processes using ensembles of constructive neural networks.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

A genetic algorithm for improving the induction of attribute-based decision graph classifiers.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

2015
Refining constructive neural networks using functionally expanded input data.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014
Imputation of missing data supported by Complete p-Partite attribute-based Decision Graphs.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Stock Closing Price Forecasting Using Ensembles of Constructive Neural Networks.
Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

2013
An incremental learning algorithm based on the K-associated graph for non-stationary data classification.
Inf. Sci., 2013

On-line prediction of the feeding phase in high-cell density cultivation of rE. coli using constructive neural networks.
Comput. Methods Programs Biomed., 2013

Methodology for inferring kinetic parameters of diesel oil HDS reactions based on scarce experimental data.
Comput. Chem. Eng., 2013

A Purity Measure Based Transductive Learning Algorithm.
Proceedings of the Advances in Neural Networks - ISNN 2013, 2013

Attribute-based Decision Graphs for multiclass data classification.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

Ensemble of complete P-partite graph classifiers for non-stationary environments.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

2012
Partially labeled data stream classification with the semi-supervised K-associated graph.
J. Braz. Comput. Soc., 2012

2011
Graph-based classification for stationary and non-stationary data.
PhD thesis, 2011

A nonparametric classification method based on K-associated graphs.
Inf. Sci., 2011

Interpreting Hidden Neurons in Boolean Constructive Neural Networks.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2011, 2011

2010
A two-class constructive neural network algorithm for continuous domains: the OffTiling algorithm.
Int. J. Knowl. Eng. Data Min., 2010

2009
Constructive Neural Network Algorithms for Feedforward Architectures Suitable for Classification Tasks.
Proceedings of the Constructive Neural Networks, 2009

A Feedforward Constructive Neural Network Algorithm for Multiclass Tasks Based on Linear Separability.
Proceedings of the Constructive Neural Networks, 2009

Classification Based on the Optimal K-Associated Network.
Proceedings of the Complex Sciences, 2009

2008
Chaotic synchronization in general network topology for scene segmentation.
Neurocomputing, 2008

MBabCoNN - A Multiclass Version of a Constructive Neural Network Algorithm Based on Linear Separability and Convex Hull.
Proceedings of the Artificial Neural Networks, 2008

2006
Using Constructive Neural Networks for Detecting Central Vestibular System Lesion.
Appl. Artif. Intell., 2006

A Comparative Evaluation of Constructive Neural Networks Methods using PRM and BCP as TLU Training Algorithms.
Proceedings of the IEEE International Conference on Systems, 2006

Two Variants of the Constructive Neural Network Tiling Algorithm.
Proceedings of the 6th International Conference on Hybrid Intelligent Systems (HIS 2006), 2006


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