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Guilherme De A. Barreto
Guilherme A. Barreto
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2020 – today
- 2024
- [c55]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 - [c54]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 - 2023
- [j41]Jessyca Almeida Bessa, Guilherme A. Barreto
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
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
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
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
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
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)
2010 – 2019
- 2019
- [j33]César Lincoln C. Mattos, Guilherme A. Barreto
A stochastic variational framework for Recurrent Gaussian Processes models. Neural Networks 112: 54-72 (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
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
- [j32]Leonardo Aguayo
Novelty Detection in Time Series Using Self-Organizing Neural Networks: A Comprehensive Evaluation. Neural Process. Lett. 47(2): 717-744 (2018) - [c49]Phelipe Wesley Oliveira, Guilherme A. Barreto
A Novel Tuning Method for PD Control of Robotic Manipulators Based on Minimum Jerk Principle. LARS/SBR/WRE 2018: 396-401 - [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] - 2017
- [j31]José Daniel A. Santos
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) - [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
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
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
Metaheuristic optimization for automatic clustering of customer-oriented supply chain data. WSOM 2017: 184-191 - 2016
- [j29]Guilherme A. Barreto
Novel approaches for parameter estimation of local linear models for dynamical system identification. Appl. Intell. 44(1): 149-165 (2016) - [j28]Guilherme A. Barreto
A Robust Extreme Learning Machine for pattern classification with outliers. Neurocomputing 176: 3-13 (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
- [j27]Amauri H. Souza Júnior, Guilherme De A. Barreto
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
Minimal Learning Machine: A novel supervised distance-based approach for regression and classification. Neurocomputing 164: 34-44 (2015) - [j25]Ricardo Gamelas Sousa
Robust classification with reject option using the self-organizing map. Neural Comput. Appl. 26(7): 1603-1619 (2015) - [j24]Guilherme A. Barreto
On the Design of Robust Linear Pattern Classifiers Based on M-Estimators. Neural Process. Lett. 42(1): 119-137 (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
- [j23]César Lincoln C. Mattos, Guilherme A. Barreto
An improved hybrid particle swarm optimization algorithm applied to economic modeling of radio resource allocation. Electron. Commer. Res. 14(1): 51-70 (2014) - [c39]David N. Coelho, Guilherme De A. Barreto
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
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
- [j22]Alberto Guillén
Data Preprocessing and Model Design for Medicine Problems. Comput. Math. Methods Medicine 2013: 625623:1 (2013) - [j21]Andre Lemme, Ananda Freire, Guilherme A. Barreto
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
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
A unifying methodology for the evaluation of neural network models on novelty detection tasks. Pattern Anal. Appl. 16(1): 83-97 (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
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
Robust Regional Modeling for Nonlinear System Identification Using Self-Organizing Maps. WSOM 2012: 215-224 - [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] - 2011
- [j16]José Everardo Bessa Maia, Guilherme De A. Barreto
Visual object tracking by an evolutionary self-organizing neural network. J. Intell. Fuzzy Syst. 22(2-3): 69-81 (2011) - [c24]Ajalmar R. da Rocha Neto, Ricardo Gamelas Sousa, Guilherme De A. Barreto
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
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 - [d2]Guilherme De A. Barreto, Ajalmar R. da Rocha Neto:
Vertebral Column. UCI Machine Learning Repository, 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) - [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
Estimating the Number of Hidden Neurons of the MLP Using Singular Value Decomposition and Principal Components Analysis: A Novel Approach. SBRN 2010: 19-24 - [d1]Ananda Freire, Marcus V. D. Veloso, Guilherme De A. Barreto:
Wall-Following Robot Navigation Data. UCI Machine Learning Repository, 2010
2000 – 2009
- 2009
- [c17]Guilherme De A. Barreto
Time Series Clustering for Anomaly Detection Using Competitive Neural Networks. WSOM 2009: 28-36 - 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) - [c16]José Everardo Bessa Maia, Guilherme De A. Barreto
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
Directly Optimizing Topology-Preserving Maps with Evolutionary Algorithms. ICONIP (1) 2008: 1180-1187 - [c14]Leonardo Aguayo
Novelty Detection in Time Series Through Self-Organizing Networks: An Empirical Evaluation of Two Different Paradigms. SBRN 2008: 129-134 - 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) - [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 - [p1]Guilherme De A. Barreto
Time Series Prediction with the Self-Organizing Map: A Review. Perspectives of Neural-Symbolic Integration 2007: 135-158 - 2006
- [j11]Guilherme De A. Barreto
Adaptive filtering with the self-organizing map: A performance comparison. Neural Networks 19(6-7): 785-798 (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 - 2005
- [j10]Guilherme De A. Barreto
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
Identification and control of dynamical systems using the self-organizing map. IEEE Trans. Neural Networks 15(5): 1244-1259 (2004) - [c10]Guilherme De A. Barreto
Competitive Neural Networks for Fault Detection and Diagnosis in 3G Cellular Systems. ICT 2004: 207-213 - [c9]Guilherme De A. Barreto
Nonstationary Time Series Prediction Using Local Models Based on Competitive Neural Networks. IEA/AIE 2004: 1146-1155 - [c8]Guilherme De A. Barreto
Predictive Modeling and Planning of Robot Trajectories Using the Self-Organizing Map. IEA/AIE 2004: 1156-1165 - 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
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
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
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) - [c7]Guilherme De A. Barreto
Nonlinear Modeling of Dynamic Systems with the Self-Organizing Map. ICANN 2002: 975-980 - [c6]Guilherme De A. Barreto
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
- [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) - [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
Storage and Recall of Complex Temporal Sequences through a Contextually Guided Self-Organizing Neural Network. IJCNN (3) 2000: 207-212
1990 – 1999
- 1999
- [j1]Guilherme De A. Barreto
Unsupervised Learning and Recall of Temporal Sequences: An Application to Robotics. Int. J. Neural Syst. 9(3): 235-242 (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
Competitive and Temporal Hebbian Learning for Production of Robot Trajectories. SBRN 1998: 96-101
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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