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ORCIDAntônio de Pádua Braga
Antônio P. Braga
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Books and Theses
- 1995
[b1]Antônio de Pádua Braga:
Design models for recursive binary neural networks. Imperial College London, UK, 1995
Journal Articles
- 2024
- [j58]Eduardo S. Ribeiro, Lourenço R. G. Araújo, Gabriel T. L. Chaves, Antônio P. Braga:
Distance-based loss function for deep feature space learning of convolutional neural networks. Comput. Vis. Image Underst. 249: 104184 (2024) - [j57]Janier Arias-Garcia
, Alan Cândido de Souza, Liliane Gade, Jones Yudi Mori, Frederico Coelho, Cristiano Leite Castro, Luiz C. B. Torres, Antônio P. Braga:
Improved Design for Hardware Implementation of Graph-Based Large Margin Classifiers for Embedded Edge Computing. IEEE Trans. Neural Networks Learn. Syst. 35(1): 1320-1329 (2024) - 2023
- [j56]Marcelo Queiroz, Frederico Coelho, Luiz C. B. Torres, Felipe V. Campos, Gabriel Lara, Wagner J. Alvarenga, Antônio de Pádua Braga:
RBF Neural Networks Design with Graph Based Structural Information from Dominating Sets. Neural Process. Lett. 55(4): 4719-4733 (2023) - 2022
- [j55]Wagner J. Alvarenga, Felipe V. Campos, Alexsander C. A. A. Costa, Turíbio Tanus Salis, Eduardo Magalhães, Luiz C. B. Torres, Antônio P. Braga:
Time domain graph-based anomaly detection approach applied to a real industrial problem. Comput. Ind. 142: 103714 (2022) - [j54]Alexsander C. A. A. Costa, Felipe V. Campos, Lourenço R. G. Araújo, Luiz C. B. Torres, Antônio de Pádua Braga:
Deep architecture for silica forecasting of a real industrial froth flotation process. Eng. Appl. Artif. Intell. 115: 105196 (2022) - [j53]Luiz C. B. Torres, Cristiano Leite Castro, Honovan P. Rocha, Gustavo Matheus de Almeida, Antônio P. Braga:
Multi-objective neural network model selection with a graph-based large margin approach. Inf. Sci. 599: 192-207 (2022) - [j52]Gustavo V. Maia, Thiago M. Coutinho, Eduardo B. Gonçalves, Gustavo Rodrigues Lacerda Silva, Eduardo M. A. M. Mendes, Marcelo M. A. M. Mendes, Sandro R. Caetano, Gustavo M. Mitt, Antônio P. Braga:
One Class Density Estimation Approach for Fault Detection and Rootcause Analysis in Computer Networks. J. Netw. Syst. Manag. 30(4): 69 (2022) - [j51]Yuri Sousa Aurelio, Gustavo Matheus de Almeida, Cristiano Leite de Castro, Antônio de Pádua Braga:
Cost-Sensitive Learning based on Performance Metric for Imbalanced Data. Neural Process. Lett. 54(4): 3097-3114 (2022) - 2021
- [j50]Alex de Assis Santos dos Santos, Luiz C. B. Torres, Lourenço R. G. Araújo, Vítor M. Hanriot, Antônio de Pádua Braga:
Neural Networks Regularization With Graph-Based Local Resampling. IEEE Access 9: 50727-50737 (2021) - [j49]Wagner J. Alvarenga, Felipe V. Campos, Vítor M. Hanriot, Eduardo B. Gonçalves, Alexsander C. A. A. Costa, Lourenço R. G. Araújo, Eduardo Magalhães, Antônio P. Braga:
Online learning of neural networks using random projections and sliding window: A case study of a real industrial process. Eng. Appl. Artif. Intell. 100: 104181 (2021) - [j48]Janier Arias-Garcia, Augusto Mafra, Liliane Gade, Frederico Coelho, Cristiano Leite Castro, Luiz C. B. Torres, Antônio de Pádua Braga:
Enhancing Performance of Gabriel Graph-Based Classifiers by a Hardware Co-Processor for Embedded System Applications. IEEE Trans. Ind. Informatics 17(2): 1186-1196 (2021) - [j47]Vasile Palade, Stefan Wermter, Ariel Ruiz-Garcia, Antônio de Pádua Braga, Clive Cheong Took:
Guest Editorial: Special Issue on Deep Representation and Transfer Learning for Smart and Connected Health. IEEE Trans. Neural Networks Learn. Syst. 32(2): 464-465 (2021) - [j46]Luiz C. B. Torres, Cristiano Leite Castro, Frederico Coelho, Antônio P. Braga:
Large Margin Gaussian Mixture Classifier With a Gabriel Graph Geometric Representation of Data Set Structure. IEEE Trans. Neural Networks Learn. Syst. 32(3): 1400-1406 (2021) - 2020
- [j45]Vitor A. M. F. Torres, D. A. C. Silva, Luiz C. B. Torres, Mateus T. Braga, M. B. R. Cardoso, V. T. Lino, Frank Sill Torres, Antônio de Pádua Braga:
Embedded real-time feature extraction for electrode inversion detection in telemedicine electrocardiograms. Biomed. Signal Process. Control. 60: 101946 (2020) - [j44]Vinícius R. Carvalho, Márcio Flávio Dutra Moraes, Antônio P. Braga, Eduardo M. A. M. Mendes:
Evaluating five different adaptive decomposition methods for EEG signal seizure detection and classification. Biomed. Signal Process. Control. 62: 102073 (2020) - [j43]Carla Caldeira Takahashi, Antônio P. Braga:
A Review of Off-Line Mode Dataset Shifts. IEEE Comput. Intell. Mag. 15(3): 16-27 (2020) - [j42]Vitor A. M. F. Torres, Brayan Rene Acevedo Jaimes, Eduardo S. Ribeiro, Mateus T. Braga, Elcio H. Shiguemori, Haroldo F. de Campos Velho, Luiz C. B. Torres, Antônio P. Braga:
Combined weightless neural network FPGA architecture for deforestation surveillance and visual navigation of UAVs. Eng. Appl. Artif. Intell. 87 (2020) - [j41]Ramon Santos Correa, Patricia Teixeira Sampaio, Rafael Utsch Braga, Victor Alberto Lambertucci, Gustavo Matheus de Almeida, Antônio de Pádua Braga:
Prediction of Mechanical Properties of Seamless Steel Tubes Using Artificial Neural Networks. Int. J. Comput. Intell. Appl. 19(4): 2050028:1-2050028:14 (2020) - [j40]Gustavo Rodrigues Lacerda Silva, Paulo Carvalho, Luiz C. B. Torres, Antônio P. Braga:
A fuzzy data reduction cluster method based on boundary information for large datasets. Neural Comput. Appl. 32(24): 18059-18068 (2020) - [j39]Frederico Coelho, Marcelo Costa, Michel Verleysen, Antônio P. Braga:
LASSO multi-objective learning algorithm for feature selection. Soft Comput. 24(17): 13209-13217 (2020) - [j38]Honovan P. Rocha, Marcelo Azevedo Costa, Antônio P. Braga:
Neural Networks Multiobjective Learning With Spherical Representation of Weights. IEEE Trans. Neural Networks Learn. Syst. 31(11): 4761-4775 (2020) - 2019
- [j37]Frederico Coelho, Cristiano Leite Castro, Antônio P. Braga, Michel Verleysen:
Semi-supervised relevance index for feature selection. Neural Comput. Appl. 31(S-2): 989-997 (2019) - [j36]Yuri Sousa Aurelio, Gustavo Matheus de Almeida, Cristiano Leite Castro, Antônio de Pádua Braga:
Learning from Imbalanced Data Sets with Weighted Cross-Entropy Function. Neural Process. Lett. 50(2): 1937-1949 (2019) - [j35]Murilo V. F. Menezes, Luiz C. B. Torres, Antônio P. Braga:
Width optimization of RBF kernels for binary classification of support vector machines: A density estimation-based approach. Pattern Recognit. Lett. 128: 1-7 (2019) - 2017
- [j34]Gustavo Rodrigues Lacerda Silva, Rafael Ribeiro de Medeiros, Brayan Rene Acevedo Jaimes, Carla Caldeira Takahashi, Douglas Alexandre Gomes Vieira, Antônio de Pádua Braga:
CUDA-Based Parallelization of Power Iteration Clustering for Large Datasets. IEEE Access 5: 27263-27271 (2017) - [j33]Alexandre W. C. Faria, Frederico Gualberto F. Coelho, Alisson Marques da Silva, Honovan P. Rocha, Gustavo Matheus de Almeida, André P. Lemos, Antônio P. Braga:
MILKDE: A new approach for multiple instance learning based on positive instance selection and kernel density estimation. Eng. Appl. Artif. Intell. 59: 196-204 (2017) - 2016
- [j32]R. N. Lima, Gustavo Matheus de Almeida, Antônio P. Braga, Marcelo Cardoso:
Trend modelling with artificial neural networks. Case study: Operating zones identification for higher SO3 incorporation in cement clinker. Eng. Appl. Artif. Intell. 54: 17-25 (2016) - [j31]Frederico Coelho, Antônio de Pádua Braga, Michel Verleysen:
A Mutual Information estimator for continuous and discrete variables applied to Feature Selection and Classification problems. Int. J. Comput. Intell. Syst. 9(4): 726-733 (2016) - [j30]Carlos Anderson Oliveira Silva, Gustavo Augusto Mascarenhas Goltz, Elcio Hideiti Shiguemori, Cristiano Leite de Castro, Haroldo F. de Campos Velho, Antônio de Pádua Braga:
Image matching applied to autonomous navigation of unmanned aerial vehicles. Int. J. High Perform. Syst. Archit. 6(4): 205-212 (2016) - 2015
- [j29]Leonardo José Silvestre, André Paim Lemos, João Pedro Braga, Antônio de Pádua Braga:
Dataset structure as prior information for parameter-free regularization of extreme learning machines. Neurocomputing 169: 288-294 (2015) - [j28]Alexandre Wagner Chagas Faria, Alisson Marques da Silva, Thiago de Souza Rodrigues, Marcelo Azevedo Costa, Antônio de Pádua Braga:
A Ranking Approach for Probe Selection and Classification of Microarray Data with Artificial Neural Networks. J. Comput. Biol. 22(10): 953-961 (2015) - 2013
- [j27]Cristiano Leite Castro, Antônio de Pádua Braga:
Novel Cost-Sensitive Approach to Improve the Multilayer Perceptron Performance on Imbalanced Data. IEEE Trans. Neural Networks Learn. Syst. 24(6): 888-899 (2013) - 2012
- [j26]Rogério Martins Gomes, Antônio de Pádua Braga, Henrique Elias Borges:
Information storage and retrieval analysis of hierarchically coupled associative memories. Inf. Sci. 195: 175-189 (2012) - [j25]Gabriela E. Soares, Henrique E. Borges, Rogério Martins Gomes, Gustavo M. Zeferino, Antônio de Pádua Braga:
Emergence of synchronicity in a self-organizing spiking neuron network: an approach via genetic algorithms. Nat. Comput. 11(3): 405-413 (2012) - [j24]Marcelo Azevedo Costa, Antônio de Pádua Braga, Benjamin Rodrigues de Menezes:
Convergence analysis of sliding mode trajectories in multi-objective neural networks learning. Neural Networks 33: 21-31 (2012) - 2011
- [j23]Frederico Coelho, Antônio de Pádua Braga, René Natowicz, Roman Rouzier:
Semi-supervised model applied to the prediction of the response to preoperative chemotherapy for breast cancer. Soft Comput. 15(6): 1137-1144 (2011) - [j22]Bruno Henrique Groenner Barbosa, Lam Thu Bui, Hussein A. Abbass, Luis Antonio Aguirre, Antônio de Pádua Braga:
The use of coevolution and the artificial immune system for ensemble learning. Soft Comput. 15(9): 1735-1747 (2011) - [j21]Thiago de Souza Rodrigues, Fernanda Caldas Cardoso, Santuza Maria Ribeiro Teixeira, Sergio Costa Oliveira, Antônio de Pádua Braga:
Protein Classification with Extended-Sequence Coding by Sliding Window. IEEE ACM Trans. Comput. Biol. Bioinform. 8(6): 1721-1726 (2011) - [j20]Bruno Henrique Groenner Barbosa, Luis Antonio Aguirre, Carlos Barreira Martinez, Antônio de Pádua Braga:
Black and Gray-Box Identification of a Hydraulic Pumping System. IEEE Trans. Control. Syst. Technol. 19(2): 398-406 (2011) - 2010
- [j19]Illya Kokshenev, Antônio de Pádua Braga:
An efficient multi-objective learning algorithm for RBF neural network. Neurocomputing 73(16-18): 2799-2808 (2010) - 2009
- [j18]André Paoliello Modenesi, Antônio de Pádua Braga:
Analysis of Time Series Novelty Detection Strategies for Synthetic and Real Data. Neural Process. Lett. 30(1): 1-17 (2009) - [j17]Bernardo Penna Resende de Carvalho, Antônio de Pádua Braga:
IP-LSSVM: A two-step sparse classifier. Pattern Recognit. Lett. 30(16): 1507-1515 (2009) - 2008
- [j16]Illya Kokshenev, Antônio de Pádua Braga:
A multi-objective approach to RBF network learning. Neurocomputing 71(7-9): 1203-1209 (2008) - [j15]Thiago Turchetti Maia, Antônio de Pádua Braga, André Carlos Ponce de Leon Ferreira de Carvalho:
Hybrid classification algorithms based on boosting and support vector machines. Kybernetes 37(9/10): 1469-1491 (2008) - 2007
- [j14]Marcelo Azevedo Costa, Antônio de Pádua Braga, Benjamin Rodrigues de Menezes:
Improving generalization of MLPs with sliding mode control and the Levenberg-Marquardt algorithm. Neurocomputing 70(7-9): 1342-1347 (2007) - [j13]Bernardo Penna Resende de Carvalho, Wilian Soares Lacerda, Antônio de Pádua Braga:
RRS + LS-SVM: a new strategy for "a priori" sample selection. Neural Comput. Appl. 16(3): 227-234 (2007) - 2006
- [j12]Murilo Saraiva de Queiroz, Roberto Coelho de Berrêdo, Antônio de Pádua Braga:
Reinforcement learning of a simple control task using the spike response model. Neurocomputing 70(1-3): 14-20 (2006) - 2005
- [j11]Estefane G. M. de Lacerda, André Carlos Ponce de Leon Ferreira de Carvalho, Antônio de Pádua Braga, Teresa Bernarda Ludermir:
Evolutionary Radial Basis Functions for Credit Assessment. Appl. Intell. 22(3): 167-181 (2005) - 2004
- [j10]Marcus Tadeu Pinheiro Silva, Antônio de Pádua Braga, Wilian Soares Lacerda:
Reconfigurable co-processor for Kanerva's sparse distributed memory. Microprocess. Microsystems 28(3): 127-134 (2004) - 2003
- [j9]Marcelo Azevedo Costa, Antônio de Pádua Braga, Benjamin Rodrigues de Menezes, Roselito de Albuquerque Teixeira, Gustavo Guimarães Parma:
Training neural networks with a multi-objective sliding mode control algorithm. Neurocomputing 51: 467-473 (2003) - 2002
- [j8]Marcelo Azevedo Costa, Antônio de Pádua Braga, Benjamin Rodrigues de Menezes:
Improving neural networks generalization with new constructive and pruning methods. J. Intell. Fuzzy Syst. 13(2-4): 75-83 (2002) - 2001
- [j7]Roselito de Albuquerque Teixeira, Antônio de Pádua Braga, Ricardo H. C. Takahashi, Rodney R. Saldanha:
Recent Advances in the MOBJ Algorithm for Training Artifical Neural Networks. Int. J. Neural Syst. 11(3): 265-270 (2001) - 2000
- [j6]Roselito de Albuquerque Teixeira, Antônio de Pádua Braga, Ricardo H. C. Takahashi, Rodney R. Saldanha:
Improving generalization of MLPs with multi-objective optimization. Neurocomputing 35(1-4): 189-194 (2000) - [j5]Roselito de Albuquerque Teixeira, Antônio de Pádua Braga, Benjamin Rodrigues de Menezes:
Control of a Robotic Manipulator Using Artificial Neural Networks with On-line Adaptation. Neural Process. Lett. 12(1): 19-31 (2000) - 1999
- [j4]Antônio de Pádua Braga, Teresa Bernarda Ludermir:
Editorial: "Artificial Neural Networks in Brazil: An Introduction to the Special Issue of IJNS". Int. J. Neural Syst. 9(3): 163-165 (1999) - [j3]Gustavo Guimarães Parma, Benjamin Rodrigues de Menezes, Antônio de Pádua Braga:
Neural Networks Learning with Sliding Mode Control: The Sliding Mode Backpropagation Algorithm. Int. J. Neural Syst. 9(3): 187-193 (1999) - [j2]Cristiane Nobre, E. Martineli, Antônio de Pádua Braga, André Carlos Ponce de Leon Ferreira de Carvalho, S. Rezende, José L. Braga, Teresa Bernarda Ludermir:
Knowledge Extraction: A Comparison between Symbolic and Connectionist Methods. Int. J. Neural Syst. 9(3): 257-264 (1999) - 1995
- [j1]Antônio de Pádua Braga, Igor Aleksander:
Geometrical treatment and statistical modelling of the distribution of patterns in the n-dimensional Boolean space. Pattern Recognit. Lett. 16(5): 507-515 (1995)
Conference and Workshop Papers
- 2021
- [c55]Danilo A. Caldeira Silva, Turíbio Tanus Salis, Antônio de Pádua Braga:
Industrial case study of causal modeling of continuous casting and lamination of steel tubes. LA-CCI 2021: 1-6 - 2019
- [c54]Lourenço R. G. Araújo, Luiz C. B. Torres, Leonardo José Silvestre, Carla Caldeira Takahashi, Antônio P. Braga:
Regularization of Extreme Learning Machines with information of spatial relations of the projected data. CoDIT 2019: 593-597 - [c53]Carla Caldeira Takahashi, Luiz C. B. Torres, Antônio P. Braga:
Gabriel Graph Transductive Approach to Dataset Shift. CoDIT 2019: 1622-1627 - [c52]Murilo V. F. Menezes, Luiz C. B. Torres, Antônio P. Braga:
Learning Regularization Parameters of Radial Basis Functions in Embedded Likelihoods Space. EPIA (2) 2019: 281-292 - [c51]Eduardo S. Ribeiro, Vitor A. M. F. Torres, Brayan James, Mateus T. Braga, Elcio H. Shiguemori, Haroldo F. de Campos Velho, Luiz C. B. Torres, Antônio P. Braga:
Weightless neural systems for deforestation surveillance and image-based navigation of UAVs in the Amazon forest. ESANN 2019 - 2018
- [c50]Carlos Natalino, Frederico Coelho, Gustavo Lacerda, Antônio P. Braga, Lena Wosinska, Paolo Monti:
A Proactive Restoration Strategy for Optical Cloud Networks Based on Failure Predictions. ICTON 2018: 1-5 - 2015
- [c49]David Pinto, André P. Lemos, Antônio P. Braga:
An affinity matrix approach for structure selection of extreme learning machines. ESANN 2015 - [c48]Honovan P. Rocha, Marcelo Azevedo Costa, Antônio P. Braga:
Training Multi-Layer Perceptron with Multi-Objective Optimization and Spherical Weights Representation. ESANN 2015 - [c47]Luiz C. B. Torres, Cristiano Leite Castro, Antônio P. Braga:
Gabriel Graph for Dataset Structure and Large Margin Classification: A Bayesian Approach. ESANN 2015 - [c46]Luiz C. B. Torres, Cristiano Leite Castro, Antônio P. Braga:
A parameterless mixture model for large margin classification. IJCNN 2015: 1-6 - 2014
- [c45]Alexandre Wagner Chagas Faria, David Menotti, André Paim Lemos, Antônio de Pádua Braga:
A new approach for multiple instance learning based on a homogeneity bag operator. ESANN 2014 - [c44]Euler G. Horta, Antônio de Pádua Braga:
An Extreme Learning Approach to Active Learning. ESANN 2014 - [c43]Leonardo José Silvestre, André Paim Lemos, João Pedro Braga, Antônio de Pádua Braga:
Parameter-free regularization in Extreme Learning Machines with affinity matrices. ESANN 2014 - [c42]Luiz C. B. Torres, André P. Lemos, Cristiano Leite Castro, Antônio P. Braga:
A Geometrical Approach for Parameter Selection of Radial Basis Functions Networks. ICANN 2014: 531-538 - 2013
- [c41]Maria Fernanda B. Wanderley, Vincent Gardeux, René Natowicz, Antônio de Pádua Braga:
GA-KDE-Bayes: an evolutionary wrapper method based on non-parametric density estimation applied to bioinformatics problems. ESANN 2013 - 2012
- [c40]Frederico Coelho, Antônio de Pádua Braga, Michel Verleysen:
Cluster homogeneity as a semi-supervised principle for feature selection using mutual information. ESANN 2012 - [c39]Luiz C. B. Torres, Cristiano Leite Castro, Antônio de Pádua Braga:
A Computational Geometry Approach for Pareto-Optimal Selection of Neural Networks. ICANN (2) 2012: 100-107 - [c38]Cristiano Leite Castro, Antônio de Pádua Braga:
Improving ANNs Performance on Unbalanced Data with an AUC-Based Learning Algorithm. ICANN (2) 2012: 314-321 - [c37]Sílvia Grasiella Moreira Almeida, Frederico Gualberto F. Coelho, Frederico Gadelha Guimarães, Antônio de Pádua Braga:
A General Approach for Adaptive Kernels in Semi-Supervised Clustering. IDEAL 2012: 508-515 - 2011
- [c36]Marcelo Azevedo Costa, Antônio de Pádua Braga:
Gradient Descent Decomposition for Multi-objective Learning. IDEAL 2011: 377-384 - 2010
- [c35]Frederico Coelho, Antônio de Pádua Braga, Michel Verleysen:
Multi-Objective Semi-Supervised Feature Selection and Model Selection Based on Pearson's Correlation Coefficient. CIARP 2010: 509-516 - [c34]Thiago Turchetti Maia, Antônio de Pádua Braga:
Introduction to Computational Intelligence Business Applications. ESANN 2010 - 2009
- [c33]Cristiano Leite Castro, Mateus Araujo Carvalho, Antônio de Pádua Braga:
An Improved Algorithm for SVMs Classification of Imbalanced Data Sets. EANN 2009: 108-118 - [c32]Tijl De Bie, Thiago Turchetti Maia, Antônio de Pádua Braga:
Machine Learning with Labeled and Unlabeled Data. ESANN 2009 - [c31]Cristiano Leite Castro, Antônio de Pádua Braga:
Artificial Neural Networks Learning in ROC Space. IJCCI 2009: 484-489 - 2008
- [c30]Antônio de Pádua Braga, Euler G. Horta, René Natowicz, Roman Rouzier, Roberto Incitti, Thiago S. Rodrigues, Marcelo Azevedo Costa, Carmen D. M. Pataro, Arben Çela:
Bayesian Classifiers for Predicting the Outcome of Breast Cancer Preoperative Chemotherapy. ANNPR 2008: 263-266 - [c29]René Natowicz, Antônio de Pádua Braga, Roberto Incitti, Euler G. Horta, Roman Rouzier, Thiago S. Rodrigues, Marcelo Azevedo Costa:
A new method of DNA probes selection and its use with multi-objective neural network for predicting the outcome of breast cancer preoperative chemotherapy. ESANN 2008: 71-76 - [c28]René Natowicz, Roberto Incitti, Roman Rouzier, Arben Çela, Antônio de Pádua Braga, Euler G. Horta, Thiago S. Rodrigues, Marcelo Azevedo Costa:
Downsizing Multigenic Predictors of the Response to Preoperative Chemotherapy in Breast Cancer. KES (2) 2008: 157-164 - [c27]Illya Kokshenev, Antônio de Pádua Braga:
A Multi-objective Learning Algorithm for RBF Neural Network. SBRN 2008: 9-14 - [c26]Cristiano Leite Castro, Antônio de Pádua Braga:
Optimization of the Area under the ROC Curve. SBRN 2008: 141-146 - [c25]Bruno Henrique Groenner Barbosa, Lam Thu Bui, Hussein A. Abbass, Luis Antonio Aguirre, Antônio de Pádua Braga:
Evolving an Ensemble of Neural Networks Using Artificial Immune Systems. SEAL 2008: 121-130 - 2007
- [c24]Illya Kokshenev, Antônio de Pádua Braga:
Complexity bounds of radial basis functions and multi-objective learning. ESANN 2007: 73-78 - [c23]Bernardo Penna Resende de Carvalho, Antônio de Pádua Braga:
A-LSSVM: an Adaline based iterative sparse LS-SVM classifier. ESANN 2007: 331-336 - [c22]Talles Henrique de Medeiros, Ricardo H. C. Takahashi, Antônio de Pádua Braga:
A new decision strategy in multi-objective training of the artificial neural networks. ESANN 2007: 555-560 - [c21]Roselito de Albuquerque Teixeira, Antônio de Pádua Braga, Rodney R. Saldanha, Ricardo H. C. Takahashi, Talles Henrique de Medeiros:
The Usage of Golden Section in Calculating the Efficient Solution in Artificial Neural Networks Training by Multi-objective Optimization. ICANN (1) 2007: 289-298 - [c20]Cristiane Neri Nobre, José Miguel Ortega, Antônio de Pádua Braga:
High Efficiency on Prediction of Translation Initiation Site (TIS) of RefSeq Sequences. BSB 2007: 138-148 - 2006
- [c19]Marcelo Azevedo Costa, Antônio de Pádua Braga:
Optimization of Neural Networks with Multi-Objective LASSO Algorithm. IJCNN 2006: 3312-3318 - [c18]Rogério Martins Gomes, Antônio de Pádua Braga, Henrique E. Borges:
Storage capacity of hierarchically coupled associative memories. SBRN 2006: 196-201 - 2005
- [c17]Bernardo Penna Resende de Carvalho, Wilian Soares Lacerda, Antônio de Pádua Braga:
A Hybrid Approach for Sparse Least Squares Support Vector Machines. HIS 2005: 323-328 - [c16]Marcelo M. Silva, Thiago Turchetti Maia, Antônio de Pádua Braga:
An evolutionary approach to Transduction in Support Vector Machines. HIS 2005: 329-334 - [c15]Wilian Soares Lacerda, Antônio de Pádua Braga:
Design of digital classifier circuits with nearest neighbour prior sample selection. HIS 2005: 531-533 - [c14]Rogério Martins Gomes, Antônio de Pádua Braga, Henrique E. Borges:
A Model for Hierarchical Associative Memories via Dynamically Coupled GBSB Neural Networks. ICANN (1) 2005: 173-178 - [c13]Leonardo Max Batista Claudino, Antônio de Pádua Braga, Arnaldo de Albuquerque Araújo, André F. Oliveira:
Unsupervised Segmentation of Text Fragments in Real Scenes. ICIAP 2005: 399-406 - 2003
- [c12]Thiago S. Rodrigues, Lucila Pacifico, Santuza Maria Ribeiro Teixeira, Sergio Oliveira, Antônio de Pádua Braga:
Amino Acid Coding with Sliding Window Technique. WOB 2003: 165-168 - 2002
- [c11]Marcelo Azevedo Costa, Antônio de Pádua Braga, Benjamin Rodrigues de Menezes, Gustavo Guimarães Parma, Roselito de Albuquerque Teixeira:
Control of Generalization with a Bi-Objective Sliding Mode Control Algorithm. SBRN 2002: 38-43 - [c10]Marcelo Azevedo Costa, Antônio de Pádua Braga, Benjamin Rodrigues de Menezes:
Improved generalization learning with Sliding Mode Control and the Levenberg-Marquadt Algorithm. SBRN 2002: 44-48 - [c9]Marcelo Azevedo Costa, Antônio de Pádua Braga, Benjamin Rodrigues de Menezes:
Constructive and Pruning Methods for Neural Network Design. SBRN 2002: 49-54 - [c8]Eber M. Duarte, Antônio de Pádua Braga, José L. Braga:
Internet economic news gathering and classification: a neural network software agent based approach. SBRN 2002: 112 - [c7]Roselito de Albuquerque Teixeira, Antônio de Pádua Braga, Ricardo H. C. Takahashi, Rodney R. Saldanha:
Decisior Implementation in Neural Model Selection by Multi-objective Optimization. SBRN 2002: 234 - 2000
- [c6]Marcelo Barros de Almeida, Antônio de Pádua Braga, João Pedro Braga:
SVM-KM: Speeding SVMs Learning with a priori Cluster Selection and k-Means. SBRN 2000: 162-167 - [c5]Roselito de Albuquerque Teixeira, Antônio de Pádua Braga, Ricardo H. C. Takahashi, Rodney R. Saldanha:
A Multi-Objective Optimization Approach for Training Artificial Neural Networks. SBRN 2000: 168-172 - 1999
- [c4]Gustavo Guimarães Parma, Benjamin Rodrigues de Menezes, Antônio de Pádua Braga:
Sliding mode backpropagation: control theory applied to neural network learning. IJCNN 1999: 1774-1778 - 1998
- [c3]Gustavo Guimarães Parma, Benjamin Rodrigues de Menezes, Antônio de Pádua Braga:
Improving Backpropagation with Sliding Mode Control. SBRN 1998: 8-13 - [c2]Antônio de Pádua Braga, Marcelo Azevedo Costa:
A General Approach for Density in the n-Dimensional Boolean Space. SBRN 1998: 161-164 - 1996
- [c1]Antônio de Pádua Braga:
A continuous approximation for the intersection of two hyper-spheres in the Boolean space. ICNN 1996: 1755-1758
Parts in Books or Collections
- 2009
- [p2]Marcelo Azevedo Costa, Thiago S. Rodrigues, Euler Guimarães Horta, Antônio de Pádua Braga, Carmen D. M. Pataro, René Natowicz, Roberto Incitti, Roman Rouzier, Arben Çela:
New Multi-Objective Algorithms for Neural Network Training Applied to Genomic Classification Data. Foundations of Computational Intelligence (1) 2009: 63-82 - 2006
- [p1]Antônio de Pádua Braga, Ricardo H. C. Takahashi, Marcelo Azevedo Costa, Roselito de Albuquerque Teixeira:
Multi-Objective Algorithms for Neural Networks Learning. Multi-Objective Machine Learning 2006: 151-171
Editorship
- 1998
- [e1]Antônio de Pádua Braga, Teresa Bernarda Ludermir:
5th Brazilian Symposium on Neural Networks (SBRN '98), 9-11 December 1998, Belo Horizonte, Brazil. IEEE Computer Society 1998, ISBN 0-8186-8629-4 [contents]
Reference Works
- 2005
- [r1]André Carlos Ponce de Leon Ferreira de Carvalho, Antônio de Pádua Braga, Teresa Bernarda Ludermir:
Credit Card Users' Data Mining. Encyclopedia of Information Science and Technology (I) 2005: 603-605
Informal and Other Publications
- 2016
- [i1]Gustavo Rodrigues Lacerda Silva, Rafael Ribeiro de Medeiros, Antônio de Pádua Braga, Douglas A. G. Vieira:
GPIC - GPU Power Iteration Cluster. CoRR abs/1604.02700 (2016)
Coauthor Index
André C. P. L. F. de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
Cristiano Leite Castro
aka: Cristiano Leite de Castro
aka: Cristiano Leite de Castro
Frederico Gualberto F. Coelho
aka: Frederico Coelho
aka: Frederico Coelho
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