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Journal Articles
- 2023
[j41]Jessyca Almeida Bessa, Guilherme A. Barreto
, Ajalmar R. da Rocha Neto:
An Outlier-Robust Growing Local Model Network for Recursive System Identification. Neural Process. Lett. 55(4): 4257-4289 (2023)- 2022
- [j40]Rômulo B. P. Drumond, Renan F. Albuquerque, Guilherme A. Barreto, Amauri H. Souza:
Pattern classification based on regional models. Appl. Soft Comput. 129: 109592 (2022) - [j39]David N. Coelho, Guilherme A. Barreto:
A Sparse Online Approach for Streaming Data Classification via Prototype-Based Kernel Models. Neural Process. Lett. 54(3): 1679-1706 (2022) - 2021
- [j38]Tiago S. Façanha, Guilherme A. Barreto, José Tarcisio Costa Filho:
A Novel Kalman Filter Formulation for Improving Tracking Performance of the Extended Kernel RLS. Circuits Syst. Signal Process. 40(3): 1397-1419 (2021) - [j37]Michael S. Duarte, Guilherme A. Barreto:
Fully adaptive dictionary for online correntropy kernel learning using proximal methods. Expert Syst. Appl. 178: 114976 (2021) - 2020
- [j36]Edmilson Q. Santos Filho, Pedro Henrique Feijo de Sousa, Pedro Pedrosa Rebouças Filho, Guilherme A. Barreto, Victor Hugo C. de Albuquerque:
Evaluation of Goat Leather Quality Based on Computational Vision Techniques. Circuits Syst. Signal Process. 39(2): 651-673 (2020) - [j35]Phelipe W. Oliveira, Guilherme A. Barreto, George A. P. Thé:
A General Framework for Optimal Tuning of PID-like Controllers for Minimum Jerk Robotic Trajectories. J. Intell. Robotic Syst. 99(3): 467-486 (2020) - [j34]Ananda L. Freire, Ajalmar R. da Rocha Neto, Guilherme A. Barreto:
On robust randomized neural networks for regression: a comprehensive review and evaluation. Neural Comput. Appl. 32(22): 16931-16950 (2020) - 2019
- [j33]César Lincoln C. Mattos, Guilherme A. Barreto:
A stochastic variational framework for Recurrent Gaussian Processes models. Neural Networks 112: 54-72 (2019) - 2018
- [j32]Leonardo Aguayo, Guilherme A. Barreto:
Novelty Detection in Time Series Using Self-Organizing Neural Networks: A Comprehensive Evaluation. Neural Process. Lett. 47(2): 717-744 (2018) - 2017
- [j31]José Daniel A. Santos, Guilherme A. Barreto:
A regularized estimation framework for online sparse LSSVR models. Neurocomputing 238: 114-125 (2017) - [j30]Marcus V. D. Veloso, José Tarcisio Costa Filho, Guilherme A. Barreto:
SOM4R: a Middleware for Robotic Applications Based on the Resource-Oriented Architecture. J. Intell. Robotic Syst. 87(3-4): 487-506 (2017) - 2016
- [j29]Guilherme A. Barreto, Luís Gustavo M. Souza:
Novel approaches for parameter estimation of local linear models for dynamical system identification. Appl. Intell. 44(1): 149-165 (2016) - [j28]Guilherme A. Barreto, Ana Luiza B. P. Barros:
A Robust Extreme Learning Machine for pattern classification with outliers. Neurocomputing 176: 3-13 (2016) - 2015
- [j27]Amauri H. Souza Júnior, Guilherme De A. Barreto, Francesco Corona:
Regional models: A new approach for nonlinear system identification via clustering of the self-organizing map. Neurocomputing 147: 31-46 (2015) - [j26]Amauri Holanda de Souza Júnior, Francesco Corona, Guilherme De A. Barreto, Yoan Miché, Amaury Lendasse:
Minimal Learning Machine: A novel supervised distance-based approach for regression and classification. Neurocomputing 164: 34-44 (2015) - [j25]Ricardo Gamelas Sousa, Ajalmar R. da Rocha Neto, Jaime S. Cardoso, Guilherme A. Barreto:
Robust classification with reject option using the self-organizing map. Neural Comput. Appl. 26(7): 1603-1619 (2015) - [j24]Guilherme A. Barreto, Ana Luiza B. P. Barros:
On the Design of Robust Linear Pattern Classifiers Based on M-Estimators. Neural Process. Lett. 42(1): 119-137 (2015) - 2014
- [j23]César Lincoln C. Mattos, Guilherme A. Barreto, Francisco Rodrigo P. Cavalcanti:
An improved hybrid particle swarm optimization algorithm applied to economic modeling of radio resource allocation. Electron. Commer. Res. 14(1): 51-70 (2014) - 2013
- [j22]Alberto Guillén, Amaury Lendasse, Guilherme A. Barreto:
Data Preprocessing and Model Design for Medicine Problems. Comput. Math. Methods Medicine 2013: 625623:1 (2013) - [j21]Andre Lemme, Ananda Freire, Guilherme A. Barreto, Jochen J. Steil:
Kinesthetic teaching of visuomotor coordination for pointing by the humanoid robot iCub. Neurocomputing 112: 179-188 (2013) - [j20]César Lincoln C. Mattos, Guilherme A. Barreto:
ARTIE and MUSCLE models: building ensemble classifiers from fuzzy ART and SOM networks. Neural Comput. Appl. 22(1): 49-61 (2013) - [j19]Cláudio M. S. Medeiros, Guilherme De A. Barreto:
A novel weight pruning method for MLP classifiers based on the MAXCORE principle. Neural Comput. Appl. 22(1): 71-84 (2013) - [j18]Ajalmar R. da Rocha Neto, Guilherme A. Barreto:
Opposite Maps: Vector Quantization Algorithms for Building Reduced-Set SVM and LSSVM Classifiers. Neural Process. Lett. 37(1): 3-19 (2013) - [j17]Guilherme De A. Barreto, Rewbenio A. Frota:
A unifying methodology for the evaluation of neural network models on novelty detection tasks. Pattern Anal. Appl. 16(1): 83-97 (2013) - 2011
- [j16]José Everardo Bessa Maia, Guilherme De A. Barreto, André L. V. Coelho:
Visual object tracking by an evolutionary self-organizing neural network. J. Intell. Fuzzy Syst. 22(2-3): 69-81 (2011) - 2010
- [j15]José B. Aragão Jr., Guilherme De A. Barreto:
Novel approaches for online playout delay prediction in VoIP applications using time series models. Comput. Electr. Eng. 36(3): 536-544 (2010) - [j14]Luís Gustavo M. Souza, Guilherme De A. Barreto:
On building local models for inverse system identification with vector quantization algorithms. Neurocomputing 73(10-12): 1993-2005 (2010) - 2008
- [j13]José Maria P. Menezes Jr., Guilherme A. Barreto:
Long-term time series prediction with the NARX network: An empirical evaluation. Neurocomputing 71(16-18): 3335-3343 (2008) - 2007
- [j12]Rewbenio A. Frota, Guilherme De A. Barreto, João Cesar M. Mota:
Anomaly detection in mobile communication networks using the self-organizing map. J. Intell. Fuzzy Syst. 18(5): 493-500 (2007) - 2006
- [j11]Guilherme De A. Barreto, Luís Gustavo M. Souza:
Adaptive filtering with the self-organizing map: A performance comparison. Neural Networks 19(6-7): 785-798 (2006) - 2005
- [j10]Guilherme De A. Barreto, João Cesar M. Mota, Luís Gustavo M. Souza, Rewbenio A. Frota, Leonardo Aguayo:
Condition monitoring of 3G cellular networks through competitive neural models. IEEE Trans. Neural Networks 16(5): 1064-1075 (2005) - 2004
- [j9]Guilherme De A. Barreto, Aluízio F. R. Araújo:
Identification and control of dynamical systems using the self-organizing map. IEEE Trans. Neural Networks 15(5): 1244-1259 (2004) - 2003
- [j8]Antonio C. Padoan Jr., Guilherme De A. Barreto, Aluízio F. R. Araújo:
Modeling and Production of Robot Trajectories Using the Temporal Parametrized Self Organizing Maps. Int. J. Neural Syst. 13(2): 119-127 (2003) - [j7]Guilherme De A. Barreto, Aluízio F. R. Araújo, Helge J. Ritter:
Self-Organizing Feature Maps for Modeling and Control of Robotic Manipulators. J. Intell. Robotic Syst. 36(4): 407-450 (2003) - [j6]Guilherme De A. Barreto, Aluízio F. R. Araújo, Stefan C. Kremer:
A Taxonomy for Spatiotemporal Connectionist Networks Revisited: The Unsupervised Case. Neural Comput. 15(6): 1255-1320 (2003) - 2002
- [j5]Aluízio F. R. Araújo, Guilherme De A. Barreto:
A Self-Organizing Context-Based Approach to the Tracking of Multiple Robot Trajectories. Appl. Intell. 17(1): 101-119 (2002) - [j4]Aluízio F. R. Araújo, Guilherme De A. Barreto:
Context in temporal sequence processing: a self-organizing approach and its application to robotics. IEEE Trans. Neural Networks 13(1): 45-57 (2002) - [j3]Guilherme De A. Barreto, Aluízio F. R. Araújo, C. Dücker, Helge J. Ritter:
A distributed robotic control system based on a temporal self-organizing neural network. IEEE Trans. Syst. Man Cybern. Part C 32(4): 347-357 (2002) - 2001
- [j2]Guilherme De A. Barreto, Aluízio F. R. Araújo:
Unsupervised Learning and Temporal Context to Recall Complex Robot Trajectories. Int. J. Neural Syst. 11(1): 11-22 (2001) - 1999
- [j1]Guilherme De A. Barreto, Aluízio F. R. Araújo:
Unsupervised Learning and Recall of Temporal Sequences: An Application to Robotics. Int. J. Neural Syst. 9(3): 235-242 (1999)
Conference and Workshop Papers
- 2024
- [c56]Rewbenio A. Frota, Marley M. B. R. Vellasco, Guilherme A. Barreto, Candida Menezes de Jesus:
Heteroassociative Mapping with Self-Organizing Maps for Probabilistic Multi-output Prediction. IJCNN 2024: 1-6 - [c55]Igor Rocha de Sousa, Guilherme A. Barreto:
Neural fractional order PID controller embedded in an 8-bit microcontroller for neonatal incubator. IJCNN 2024: 1-8 - [c54]Rewbenio A. Frota, Guilherme A. Barreto, Marley M. B. R. Vellasco, Candida Menezes de Jesus:
New Cloth Unto an Old Garment: SOM for Regeneration Learning. WSOM+ 2024: 1-10 - 2019
- [c53]Renan Bessa, Guilherme A. Barreto:
Robust Echo State Network for Recursive System Identification. IWANN (1) 2019: 247-258 - [c52]Lucas Cabral, Guilherme A. Barreto, José Maria Monteiro:
Classificação de Estados Epilépticos em Sinais de EEG utilizando Detecção de Anomalias. SBBD 2019: 145-156 - [c51]Diego P. Sousa, Guilherme A. Barreto, Charles C. Cavalcante, Cláudio M. S. Medeiros:
LVQ-type Classifiers for Condition Monitoring of Induction Motors: A Performance Comparison. WSOM+ 2019: 130-139 - [c50]David N. Coelho, Guilherme A. Barreto:
Approximate Linear Dependence as a Design Method for Kernel Prototype-Based Classifiers. WSOM+ 2019: 241-250 - 2018
- [c49]Phelipe Wesley Oliveira, Guilherme A. Barreto, George A. P. Thé:
A Novel Tuning Method for PD Control of Robotic Manipulators Based on Minimum Jerk Principle. LARS/SBR/WRE 2018: 396-401 - 2017
- [c48]Marcelo B. A. Veras, Diego P. P. Mesquita, João P. P. Gomes, Amauri H. Souza Júnior, Guilherme A. Barreto:
Forward Stagewise Regression on Incomplete Datasets. IWANN (1) 2017: 386-395 - [c47]César Lincoln C. Mattos, Guilherme A. Barreto, Gonzalo Acuña:
Randomized Neural Networks for Recursive System Identification in the Presence of Outliers: A Performance Comparison. IWANN (1) 2017: 603-615 - [c46]David N. Coelho, Guilherme A. Barreto, Cláudio M. S. Medeiros:
Detection of short circuit faults in 3-phase converter-fed induction motors using kernel SOMs. WSOM 2017: 118-124 - [c45]César Lincoln C. Mattos, Guilherme A. Barreto, Dennis Horstkemper, Bernd Hellingrath:
Metaheuristic optimization for automatic clustering of customer-oriented supply chain data. WSOM 2017: 184-191 - 2016
- [c44]Humberto I. Fontinele, Davyd B. Melo, Guilherme A. Barreto:
Local Models for Learning Inverse Kinematics of Redundant Robots: A Performance Comparison. WSOM 2016: 177-187 - [c43]César Lincoln C. Mattos, Zhenwen Dai, Andreas C. Damianou, Jeremy Forth, Guilherme A. Barreto, Neil D. Lawrence:
Recurrent Gaussian Processes. ICLR (Poster) 2016 - 2015
- [c42]César Lincoln C. Mattos, José Daniel A. Santos, Guilherme A. Barreto:
An Empirical Evaluation of Robust Gaussian Process Models for System Identification. IDEAL 2015: 172-180 - [c41]José Daniel A. Santos, Guilherme A. Barreto:
A Novel Recursive Solution to LS-SVR for Robust Identification of Dynamical Systems. IDEAL 2015: 191-198 - [c40]José Daniel A. Santos, César Lincoln C. Mattos, Guilherme A. Barreto:
Performance Evaluation of Least Squares SVR in Robust Dynamical System Identification. IWANN (2) 2015: 422-435 - 2014
- [c39]David N. Coelho, Guilherme De A. Barreto, Cláudio M. S. Medeiros, José Daniel Alencar Santos:
Performance comparison of classifiers in the detection of short circuit incipient fault in a three-phase induction motor. CIES 2014: 42-48 - [c38]Ananda Freire, Guilherme A. Barreto:
A new model selection approach for the ELM network using metaheuristic optimization. ESANN 2014 - [c37]Ricardo Gamelas Sousa, Ajalmar R. da Rocha Neto, Guilherme A. Barreto, Jaime S. Cardoso, Miguel T. Coimbra:
reject option paradigm for the reduction of support vectors. ESANN 2014 - [c36]Ricardo Gamelas Sousa, Ajalmar R. da Rocha Neto, Jaime S. Cardoso, Guilherme De A. Barreto:
Classification with Reject Option Using the Self-Organizing Map. ICANN 2014: 105-112 - [c35]César Lincoln C. Mattos, José Daniel A. Santos, Guilherme A. Barreto:
Improved Adaline Networks for Robust Pattern Classification. ICANN 2014: 579-586 - [c34]José Daniel A. Santos, César Lincoln C. Mattos, Guilherme De A. Barreto:
A Novel Recursive Kernel-Based Algorithm for Robust Pattern Classification. IDEAL 2014: 150-157 - [c33]Luiz A. Soares Filho, Guilherme A. Barreto:
On the efficient design of a prototype-based classifier using differential evolution. SDE 2014: 57-64 - 2013
- [c32]Ana Luiza Bessa de Paula Barros, Guilherme A. Barreto:
Building a Robust Extreme Learning Machine for Classification in the Presence of Outliers. HAIS 2013: 588-597 - [c31]Amauri Holanda de Souza Júnior, Francesco Corona, Yoan Miche, Amaury Lendasse, Guilherme A. Barreto, Olli Simula:
Minimal Learning Machine: A New Distance-Based Method for Supervised Learning. IWANN (1) 2013: 408-416 - [c30]Ana Luiza Bessa de Paula Barros, Guilherme A. Barreto:
Improving the Classification Performance of Optimal Linear Associative Memory in the Presence of Outliers. IWANN (1) 2013: 622-632 - 2012
- [c29]Ananda Freire, Andre Lemme, Jochen J. Steil, Guilherme A. Barreto:
Learning visuo-motor coordination for pointing without depth calculation. ESANN 2012 - [c28]Amauri Holanda de Souza Júnior, Guilherme De A. Barreto:
Regional Models for Nonlinear System Identification Using the Self-Organizing Map. IDEAL 2012: 717-724 - [c27]Ajalmar R. da Rocha Neto, Guilherme De A. Barreto:
Fast Opposite Maps: An Iterative SOM-Based Method for Building Reduced-Set SVMs. IDEAL 2012: 725-732 - [c26]Ajalmar R. da Rocha Neto, Guilherme A. Barreto:
Opposite Maps for Hard Margin Support Vector Machines. WSOM 2012: 65-74 - [c25]Amauri Holanda de Souza Júnior, Francesco Corona, Guilherme A. Barreto:
Robust Regional Modeling for Nonlinear System Identification Using Self-Organizing Maps. WSOM 2012: 215-224 - 2011
- [c24]Ajalmar R. da Rocha Neto, Ricardo Gamelas Sousa, Guilherme De A. Barreto, Jaime S. Cardoso:
Diagnostic of Pathology on the Vertebral Column with Embedded Reject Option. IbPRIA 2011: 588-595 - [c23]Ajalmar R. da Rocha Neto, Guilherme De A. Barreto:
A Novel Heuristic for Building Reduced-Set SVMs Using the Self-Organizing Map. IWANN (1) 2011: 97-104 - [c22]José Everardo Bessa Maia, Guilherme De A. Barreto, André Luís Vasconcelos Coelho:
Evolving a Self-Organizing Feature Map for Visual Object Tracking. WSOM 2011: 121-130 - [c21]Ana Cristina C. Silva, Ana Cristina P. Macedo, Guilherme De A. Barreto:
A SOM-Based Analysis of Early Prosodic Acquisition of English by Brazilian Learners: Preliminary Results. WSOM 2011: 267-276 - 2010
- [c20]Everardo Maia, Guilherme De A. Barreto, André Luís Vasconcelos Coelho:
Image registration by the extended evolutionary self-organizing map. ESANN 2010 - [c19]Luís Gustavo M. Souza, Guilherme De A. Barreto:
Multiple Local Models for System Identification Using Vector Quantization Algorithms. ESANN 2010 - [c18]José Daniel A. Santos, Guilherme De A. Barreto, Cláudio M. S. Medeiros:
Estimating the Number of Hidden Neurons of the MLP Using Singular Value Decomposition and Principal Components Analysis: A Novel Approach. SBRN 2010: 19-24 - 2009
- [c17]Guilherme De A. Barreto, Leonardo Aguayo:
Time Series Clustering for Anomaly Detection Using Competitive Neural Networks. WSOM 2009: 28-36 - 2008
- [c16]José Everardo Bessa Maia, Guilherme De A. Barreto, André L. V. Coelho:
On Self-Organizing Feature Map (SOFM) Formation by Direct Optimization Through a Genetic Algorithm. HIS 2008: 661-666 - [c15]José Everardo Bessa Maia, André L. V. Coelho, Guilherme De A. Barreto:
Directly Optimizing Topology-Preserving Maps with Evolutionary Algorithms. ICONIP (1) 2008: 1180-1187 - [c14]Leonardo Aguayo, Guilherme De A. Barreto:
Novelty Detection in Time Series Through Self-Organizing Networks: An Empirical Evaluation of Two Different Paradigms. SBRN 2008: 129-134 - 2007
- [c13]Cláudio M. S. Medeiros, Guilherme De A. Barreto:
An Efficient Method for Pruning the Multilayer Perceptron Based on the Correlation of Errors. ICANN (1) 2007: 219-228 - [c12]Cláudio M. S. Medeiros, Guilherme De A. Barreto:
Pruning the Multilayer Perceptron through the Correlation of Backpropagated Errors. ISDA 2007: 64-69 - 2006
- [c11]José Maria P. Menezes Jr., Guilherme De A. Barreto:
A New Look at Nonlinear Time Series Prediction with NARX Recurrent Neural Network. SBRN 2006: 160-165 - 2004
- [c10]Guilherme De A. Barreto, João Cesar M. Mota, Luís Gustavo M. Souza, Rewbenio A. Frota, Leonardo Aguayo, José S. Yamamoto, Pedro Eduardo de Oliveira Macedo:
Competitive Neural Networks for Fault Detection and Diagnosis in 3G Cellular Systems. ICT 2004: 207-213 - [c9]Guilherme De A. Barreto, João Cesar M. Mota, Luís Gustavo M. Souza, Rewbenio A. Frota:
Nonstationary Time Series Prediction Using Local Models Based on Competitive Neural Networks. IEA/AIE 2004: 1146-1155 - [c8]Guilherme De A. Barreto, Aluízio F. R. Araújo:
Predictive Modeling and Planning of Robot Trajectories Using the Self-Organizing Map. IEA/AIE 2004: 1156-1165 - 2002
- [c7]Guilherme De A. Barreto, Aluízio F. R. Araújo:
Nonlinear Modeling of Dynamic Systems with the Self-Organizing Map. ICANN 2002: 975-980 - [c6]Guilherme De A. Barreto, Aluízio F. R. Araújo:
Temporal associative memory and function approximation with the self-organizing map. NNSP 2002: 109-118 - [c5]Antonio C. Padoan Jr., Aluízio F. R. Araújo, Guilherme De A. Barreto:
Dynamic Modeling of Robotic Trajectories Using the Parametrized SOM. SBRN 2002: 195 - 2001
- [c4]Guilherme A. Barreto, Aluízio Fausto Ribeiro Araújo, C. Dücker, Helge J. Ritter:
A distributed robotic control system based on a temporal self-organizing neural network. SMC 2001: 335-340 - 2000
- [c3]Guilherme De A. Barreto, Aluízio F. R. Araújo:
Storage and Recall of Complex Temporal Sequences through a Contextually Guided Self-Organizing Neural Network. IJCNN (3) 2000: 207-212 - 1999
- [c2]Guilherme De A. Barreto, Aluízio F. R. Araújo:
Unsupervised context-based learning of multiple temporal sequences. IJCNN 1999: 1102-1106 - 1998
- [c1]Guilherme De A. Barreto, Aluízio F. R. Araújo:
Competitive and Temporal Hebbian Learning for Production of Robot Trajectories. SBRN 1998: 96-101
Parts in Books or Collections
- 2007
- [p1]Guilherme De A. Barreto:
Time Series Prediction with the Self-Organizing Map: A Review. Perspectives of Neural-Symbolic Integration 2007: 135-158
Editorship
- 2018
- [e2]Guilherme A. Barreto, Ricardo Coelho:
Fuzzy Information Processing - 37th Conference of the North American Fuzzy Information Processing Society, NAFIPS 2018, Fortaleza, Brazil, July 4-6, 2018, Proceedings. Communications in Computer and Information Science 831, Springer 2018, ISBN 978-3-319-95311-3 [contents] - 2012
- [e1]Hujun Yin, José Alfredo Ferreira Costa, Guilherme De A. Barreto:
Intelligent Data Engineering and Automated Learning - IDEAL 2012 - 13th International Conference, Natal, Brazil, August 29-31, 2012. Proceedings. Lecture Notes in Computer Science 7435, Springer 2012, ISBN 978-3-642-32638-7 [contents]
Data and Artifacts
- 2011
- [d2]Guilherme De A. Barreto, Ajalmar R. da Rocha Neto:
Vertebral Column. UCI Machine Learning Repository, 2011
- 2010
- [d1]Ananda Freire, Marcus V. D. Veloso, Guilherme De A. Barreto:
Wall-Following Robot Navigation Data. UCI Machine Learning Repository, 2010
Coauthor Index
Aluízio F. R. Araújo
aka: Aluízio Fausto Ribeiro Araújo
aka: Aluízio Fausto Ribeiro Araújo
José Daniel A. Santos
aka: José Daniel Alencar Santos
aka: José Daniel Alencar Santos
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