Geometrical treatment and statistical modelling of the distribution of patterns in the n-dimensional Boolean space. - Antônio de Pádua Braga; Igor Aleksander (Pattern Recognit. Lett., 1995)

Design models for recursive binary neural networks. - Antônio de Pádua Braga (1995)

A continuous approximation for the intersection of two hyper-spheres in the Boolean space. - Antônio de Pádua Braga (ICNN, 1996)

A General Approach for Density in the n-Dimensional Boolean Space. - Antônio de Pádua Braga; Marcelo Azevedo Costa (SBRN, 1998)

Improving Backpropagation with Sliding Mode Control. - Gustavo Guimarães Parma; Benjamin Rodrigues de Menezes; Antônio de Pádua Braga (SBRN, 1998)

Sliding mode backpropagation: control theory applied to neural network learning. - Gustavo Guimarães Parma; Benjamin Rodrigues de Menezes; Antônio de Pádua Braga (IJCNN, 1999)

Editorial: "Artificial Neural Networks in Brazil: An Introduction to the Special Issue of IJNS". - Antônio de Pádua Braga; Teresa Bernarda Ludermir (Int. J. Neural Syst., 1999)

Knowledge Extraction: A Comparison between Symbolic and Connectionist Methods. - Cristiane Nobre; E. Martineli; Antônio de Pádua Braga; André Carlos Ponce de Leon Ferreira de Carvalho; S. Rezende; José L. Braga; Teresa Bernarda Ludermir (Int. J. Neural Syst., 1999)

Neural Networks Learning with Sliding Mode Control: The Sliding Mode Backpropagation Algorithm. - Gustavo Guimarães Parma; Benjamin Rodrigues de Menezes; Antônio de Pádua Braga (Int. J. Neural Syst., 1999)

SVM-KM: Speeding SVMs Learning with a priori Cluster Selection and k-Means. - Marcelo Barros de Almeida; Antônio de Pádua Braga; João Pedro Braga (SBRN, 2000)

A Multi-Objective Optimization Approach for Training Artificial Neural Networks. - Roselito de Albuquerque Teixeira; Antônio de Pádua Braga; Ricardo H. C. Takahashi; Rodney R. Saldanha (SBRN, 2000)

Improving generalization of MLPs with multi-objective optimization. - Roselito de Albuquerque Teixeira; Antônio de Pádua Braga; Ricardo H. C. Takahashi; Rodney R. Saldanha (Neurocomputing, 2000)

Control of a Robotic Manipulator Using Artificial Neural Networks with On-line Adaptation. - Roselito de Albuquerque Teixeira; Antônio de Pádua Braga; Benjamin Rodrigues de Menezes (Neural Process. Lett., 2000)

Recent Advances in the MOBJ Algorithm for Training Artifical Neural Networks. - Roselito de Albuquerque Teixeira; Antônio de Pádua Braga; Ricardo H. C. Takahashi; Rodney R. Saldanha (Int. J. Neural Syst., 2001)

Improved generalization learning with Sliding Mode Control and the Levenberg-Marquadt Algorithm. - Marcelo Azevedo Costa; Antônio de Pádua Braga; Benjamin Rodrigues de Menezes (SBRN, 2002)

Constructive and Pruning Methods for Neural Network Design. - Marcelo Azevedo Costa; Antônio de Pádua Braga; Benjamin Rodrigues de Menezes (SBRN, 2002)

Control of Generalization with a Bi-Objective Sliding Mode Control Algorithm. - Marcelo Azevedo Costa; Antônio de Pádua Braga; Benjamin Rodrigues de Menezes; Gustavo Guimarães Parma; Roselito de Albuquerque Teixeira (SBRN, 2002)

Internet economic news gathering and classification: a neural network software agent based approach. - Eber M. Duarte; Antônio de Pádua Braga; José L. Braga (SBRN, 2002)

Decisior Implementation in Neural Model Selection by Multi-objective Optimization. - Roselito de Albuquerque Teixeira; Antônio de Pádua Braga; Ricardo H. C. Takahashi; Rodney R. Saldanha (SBRN, 2002)

Improving neural networks generalization with new constructive and pruning methods. - Marcelo Azevedo Costa; Antônio de Pádua Braga; Benjamin Rodrigues de Menezes (J. Intell. Fuzzy Syst., 2002)

Amino Acid Coding with Sliding Window Technique. - Thiago S. Rodrigues; Lucila Pacifico; Santuza Maria Ribeiro Teixeira; Sergio Oliveira; Antônio de Pádua Braga (WOB, 2003)

Training neural networks with a multi-objective sliding mode control algorithm. - Marcelo Azevedo Costa; Antônio de Pádua Braga; Benjamin Rodrigues de Menezes; Roselito de Albuquerque Teixeira; Gustavo Guimarães Parma (Neurocomputing, 2003)

Reconfigurable co-processor for Kanerva's sparse distributed memory. - Marcus Tadeu Pinheiro Silva; Antônio de Pádua Braga; Wilian Soares Lacerda (Microprocess. Microsystems, 2004)

Credit Card Users' Data Mining. - André Carlos Ponce de Leon Ferreira de Carvalho; Antônio de Pádua Braga; Teresa Bernarda Ludermir (Encyclopedia of Information Science and Technology (I), 2005)

A Hybrid Approach for Sparse Least Squares Support Vector Machines. - Bernardo Penna Resende de Carvalho; Wilian Soares Lacerda; Antônio de Pádua Braga (HIS, 2005)

Design of digital classifier circuits with nearest neighbour prior sample selection. - Wilian Soares Lacerda; Antônio de Pádua Braga (HIS, 2005)

An evolutionary approach to Transduction in Support Vector Machines. - Marcelo M. Silva; Thiago Turchetti Maia; Antônio de Pádua Braga (HIS, 2005)

A Model for Hierarchical Associative Memories via Dynamically Coupled GBSB Neural Networks. - Rogério Martins Gomes; Antônio de Pádua Braga; Henrique E. Borges (ICANN (1), 2005)

Unsupervised Segmentation of Text Fragments in Real Scenes. - Leonardo Max Batista Claudino; Antônio de Pádua Braga; Arnaldo de Albuquerque Araújo; André F. Oliveira (ICIAP, 2005)

Evolutionary Radial Basis Functions for Credit Assessment. - Estefane G. M. de Lacerda; André Carlos Ponce de Leon Ferreira de Carvalho; Antônio de Pádua Braga; Teresa Bernarda Ludermir (Appl. Intell., 2005)

Optimization of Neural Networks with Multi-Objective LASSO Algorithm. - Marcelo Azevedo Costa; Antônio de Pádua Braga (IJCNN, 2006)

Storage capacity of hierarchically coupled associative memories. - Rogério Martins Gomes; Antônio de Pádua Braga; Henrique E. Borges (SBRN, 2006)

Reinforcement learning of a simple control task using the spike response model. - Murilo Saraiva de Queiroz; Roberto Coelho de Berrêdo; Antônio de Pádua Braga (Neurocomputing, 2006)

Multi-Objective Algorithms for Neural Networks Learning. - Antônio de Pádua Braga; Ricardo H. C. Takahashi; Marcelo Azevedo Costa; Roselito de Albuquerque Teixeira (Multi-Objective Machine Learning, 2006)

A-LSSVM: an Adaline based iterative sparse LS-SVM classifier. - Bernardo Penna Resende de Carvalho; Antônio de Pádua Braga (ESANN, 2007)

Complexity bounds of radial basis functions and multi-objective learning. - Illya Kokshenev; Antônio de Pádua Braga (ESANN, 2007)

A new decision strategy in multi-objective training of the artificial neural networks. - Talles Henrique de Medeiros; Ricardo H. C. Takahashi; Antônio de Pádua Braga (ESANN, 2007)

The Usage of Golden Section in Calculating the Efficient Solution in Artificial Neural Networks Training by Multi-objective Optimization. - Roselito de Albuquerque Teixeira; Antônio de Pádua Braga; Rodney R. Saldanha; Ricardo H. C. Takahashi; Talles Henrique de Medeiros (ICANN (1), 2007)

High Efficiency on Prediction of Translation Initiation Site (TIS) of RefSeq Sequences. - Cristiane Neri Nobre; José Miguel Ortega; Antônio de Pádua Braga (BSB, 2007)

Improving generalization of MLPs with sliding mode control and the Levenberg-Marquardt algorithm. - Marcelo Azevedo Costa; Antônio de Pádua Braga; Benjamin Rodrigues de Menezes (Neurocomputing, 2007)

RRS + LS-SVM: a new strategy for "a priori" sample selection. - Bernardo Penna Resende de Carvalho; Wilian Soares Lacerda; Antônio de Pádua Braga (Neural Comput. Appl., 2007)

Bayesian Classifiers for Predicting the Outcome of Breast Cancer Preoperative Chemotherapy. - 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 (ANNPR, 2008)

A new method of DNA probes selection and its use with multi-objective neural network for predicting the outcome of breast cancer preoperative chemotherapy. - René Natowicz; Antônio de Pádua Braga; Roberto Incitti; Euler G. Horta; Roman Rouzier; Thiago S. Rodrigues; Marcelo Azevedo Costa (ESANN, 2008)

Downsizing Multigenic Predictors of the Response to Preoperative Chemotherapy in Breast Cancer. - René Natowicz; Roberto Incitti; Roman Rouzier; Arben Çela; Antônio de Pádua Braga; Euler G. Horta; Thiago S. Rodrigues; Marcelo Azevedo Costa (KES (2), 2008)

Optimization of the Area under the ROC Curve. - Cristiano Leite Castro; Antônio de Pádua Braga (SBRN, 2008)

A Multi-objective Learning Algorithm for RBF Neural Network. - Illya Kokshenev; Antônio de Pádua Braga (SBRN, 2008)

Evolving an Ensemble of Neural Networks Using Artificial Immune Systems. - Bruno Henrique Groenner Barbosa; Lam Thu Bui; Hussein A. Abbass; Luis Antonio Aguirre; Antônio de Pádua Braga (SEAL, 2008)

A multi-objective approach to RBF network learning. - Illya Kokshenev; Antônio de Pádua Braga (Neurocomputing, 2008)

Hybrid classification algorithms based on boosting and support vector machines. - Thiago Turchetti Maia; Antônio de Pádua Braga; André Carlos Ponce de Leon Ferreira de Carvalho (Kybernetes, 2008)

An Improved Algorithm for SVMs Classification of Imbalanced Data Sets. - Cristiano Leite Castro; Mateus Araujo Carvalho; Antônio de Pádua Braga (EANN, 2009)

Machine Learning with Labeled and Unlabeled Data. - Tijl De Bie; Thiago Turchetti Maia; Antônio de Pádua Braga (ESANN, 2009)

Artificial Neural Networks Learning in ROC Space. - Cristiano Leite Castro; Antônio de Pádua Braga (IJCCI, 2009)

Analysis of Time Series Novelty Detection Strategies for Synthetic and Real Data. - André Paoliello Modenesi; Antônio de Pádua Braga (Neural Process. Lett., 2009)

IP-LSSVM: A two-step sparse classifier. - Bernardo Penna Resende de Carvalho; Antônio de Pádua Braga (Pattern Recognit. Lett., 2009)

New Multi-Objective Algorithms for Neural Network Training Applied to Genomic Classification Data. - 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 (Foundations of Computational Intelligence (1), 2009)

Multi-Objective Semi-Supervised Feature Selection and Model Selection Based on Pearson's Correlation Coefficient. - Frederico Coelho; Antônio de Pádua Braga; Michel Verleysen (CIARP, 2010)

Introduction to Computational Intelligence Business Applications. - Thiago Turchetti Maia; Antônio de Pádua Braga (ESANN, 2010)

An efficient multi-objective learning algorithm for RBF neural network. - Illya Kokshenev; Antônio de Pádua Braga (Neurocomputing, 2010)

Gradient Descent Decomposition for Multi-objective Learning. - Marcelo Azevedo Costa; Antônio de Pádua Braga (IDEAL, 2011)

The use of coevolution and the artificial immune system for ensemble learning. - Bruno Henrique Groenner Barbosa; Lam Thu Bui; Hussein A. Abbass; Luis Antonio Aguirre; Antônio de Pádua Braga (Soft Comput., 2011)

Semi-supervised model applied to the prediction of the response to preoperative chemotherapy for breast cancer. - Frederico Coelho; Antônio de Pádua Braga; René Natowicz; Roman Rouzier (Soft Comput., 2011)

Protein Classification with Extended-Sequence Coding by Sliding Window. - Thiago de Souza Rodrigues; Fernanda Caldas Cardoso; Santuza Maria Ribeiro Teixeira; Sergio Costa Oliveira; Antônio de Pádua Braga (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

Black and Gray-Box Identification of a Hydraulic Pumping System. - Bruno Henrique Groenner Barbosa; Luis Antonio Aguirre; Carlos Barreira Martinez; Antônio de Pádua Braga (IEEE Trans. Control. Syst. Technol., 2011)

Cluster homogeneity as a semi-supervised principle for feature selection using mutual information. - Frederico Coelho; Antônio de Pádua Braga; Michel Verleysen (ESANN, 2012)

Improving ANNs Performance on Unbalanced Data with an AUC-Based Learning Algorithm. - Cristiano Leite Castro; Antônio de Pádua Braga (ICANN (2), 2012)

A Computational Geometry Approach for Pareto-Optimal Selection of Neural Networks. - Luiz C. B. Torres; Cristiano Leite Castro; Antônio de Pádua Braga (ICANN (2), 2012)

A General Approach for Adaptive Kernels in Semi-Supervised Clustering. - Sílvia Grasiella Moreira Almeida; Frederico Gualberto F. Coelho; Frederico Gadelha Guimarães; Antônio de Pádua Braga (IDEAL, 2012)

Information storage and retrieval analysis of hierarchically coupled associative memories. - Rogério Martins Gomes; Antônio de Pádua Braga; Henrique Elias Borges (Inf. Sci., 2012)

Emergence of synchronicity in a self-organizing spiking neuron network: an approach via genetic algorithms. - Gabriela E. Soares; Henrique E. Borges; Rogério Martins Gomes; Gustavo M. Zeferino; Antônio de Pádua Braga (Nat. Comput., 2012)

Convergence analysis of sliding mode trajectories in multi-objective neural networks learning. - Marcelo Azevedo Costa; Antônio de Pádua Braga; Benjamin Rodrigues de Menezes (Neural Networks, 2012)

GA-KDE-Bayes: an evolutionary wrapper method based on non-parametric density estimation applied to bioinformatics problems. - Maria Fernanda B. Wanderley; Vincent Gardeux; René Natowicz; Antônio de Pádua Braga (ESANN, 2013)

Novel Cost-Sensitive Approach to Improve the Multilayer Perceptron Performance on Imbalanced Data. - Cristiano Leite Castro; Antônio de Pádua Braga (IEEE Trans. Neural Networks Learn. Syst., 2013)

A new approach for multiple instance learning based on a homogeneity bag operator. - Alexandre Wagner Chagas Faria; David Menotti; André Paim Lemos; Antônio de Pádua Braga (ESANN, 2014)

An Extreme Learning Approach to Active Learning. - Euler G. Horta; Antônio de Pádua Braga (ESANN, 2014)

Parameter-free regularization in Extreme Learning Machines with affinity matrices. - Leonardo José Silvestre; André Paim Lemos; João Pedro Braga; Antônio de Pádua Braga (ESANN, 2014)

A Geometrical Approach for Parameter Selection of Radial Basis Functions Networks. - Luiz C. B. Torres; André P. Lemos; Cristiano Leite Castro; Antônio P. Braga (ICANN, 2014)

An affinity matrix approach for structure selection of extreme learning machines. - David Pinto 002; André P. Lemos; Antônio P. Braga (ESANN, 2015)

Training Multi-Layer Perceptron with Multi-Objective Optimization and Spherical Weights Representation. - Honovan P. Rocha; Marcelo Azevedo Costa; Antônio P. Braga (ESANN, 2015)

Gabriel Graph for Dataset Structure and Large Margin Classification: A Bayesian Approach. - Luiz C. B. Torres; Cristiano Leite Castro; Antônio P. Braga (ESANN, 2015)

A parameterless mixture model for large margin classification. - Luiz C. B. Torres; Cristiano Leite Castro; Antônio P. Braga (IJCNN, 2015)

Dataset structure as prior information for parameter-free regularization of extreme learning machines. - Leonardo José Silvestre; André Paim Lemos; João Pedro Braga; Antônio de Pádua Braga (Neurocomputing, 2015)

A Ranking Approach for Probe Selection and Classification of Microarray Data with Artificial Neural Networks. - Alexandre Wagner Chagas Faria; Alisson Marques da Silva; Thiago de Souza Rodrigues; Marcelo Azevedo Costa; Antônio de Pádua Braga (J. Comput. Biol., 2015)

GPIC - GPU Power Iteration Cluster. - Gustavo Rodrigues Lacerda Silva; Rafael Ribeiro de Medeiros; Antônio de Pádua Braga; Douglas A. G. Vieira (CoRR, 2016)

Trend modelling with artificial neural networks. Case study: Operating zones identification for higher SO3 incorporation in cement clinker. - R. N. Lima; Gustavo Matheus de Almeida; Antônio P. Braga; Marcelo Cardoso (Eng. Appl. Artif. Intell., 2016)

A Mutual Information estimator for continuous and discrete variables applied to Feature Selection and Classification problems. - Frederico Coelho; Antônio de Pádua Braga; Michel Verleysen (Int. J. Comput. Intell. Syst., 2016)

Image matching applied to autonomous navigation of unmanned aerial vehicles. - Carlos Anderson Oliveira Silva; Gustavo Augusto Mascarenhas Goltz; Elcio Hideiti Shiguemori; Cristiano Leite de Castro; Haroldo F. de Campos Velho; Antônio de Pádua Braga (Int. J. High Perform. Syst. Archit., 2016)

CUDA-Based Parallelization of Power Iteration Clustering for Large Datasets. - Gustavo Rodrigues Lacerda Silva; Rafael Ribeiro de Medeiros; Brayan Rene Acevedo Jaimes; Carla Caldeira Takahashi; Douglas Alexandre Gomes Vieira; Antônio de Pádua Braga (IEEE Access, 2017)

MILKDE: A new approach for multiple instance learning based on positive instance selection and kernel density estimation. - 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 (Eng. Appl. Artif. Intell., 2017)

A Proactive Restoration Strategy for Optical Cloud Networks Based on Failure Predictions. - Carlos Natalino; Frederico Coelho; Gustavo Lacerda; Antônio P. Braga; Lena Wosinska; Paolo Monti 001 (ICTON, 2018)

Regularization of Extreme Learning Machines with information of spatial relations of the projected data. - Lourenço R. G. Araújo; Luiz C. B. Torres; Leonardo José Silvestre; Carla Caldeira Takahashi; Antônio P. Braga (CoDIT, 2019)

Gabriel Graph Transductive Approach to Dataset Shift. - Carla Caldeira Takahashi; Luiz C. B. Torres; Antônio P. Braga (CoDIT, 2019)

Learning Regularization Parameters of Radial Basis Functions in Embedded Likelihoods Space. - Murilo V. F. Menezes; Luiz C. B. Torres; Antônio P. Braga (EPIA (2), 2019)

Weightless neural systems for deforestation surveillance and image-based navigation of UAVs in the Amazon forest. - 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 (ESANN, 2019)

Semi-supervised relevance index for feature selection. - Frederico Coelho; Cristiano Leite Castro; Antônio P. Braga; Michel Verleysen (Neural Comput. Appl., 2019)

Learning from Imbalanced Data Sets with Weighted Cross-Entropy Function. - Yuri Sousa Aurelio; Gustavo Matheus de Almeida; Cristiano Leite Castro; Antônio de Pádua Braga (Neural Process. Lett., 2019)

Width optimization of RBF kernels for binary classification of support vector machines: A density estimation-based approach. - Murilo V. F. Menezes; Luiz C. B. Torres; Antônio P. Braga (Pattern Recognit. Lett., 2019)

Evaluating five different adaptive decomposition methods for EEG signal seizure detection and classification. - Vinícius R. Carvalho; Márcio Flávio Dutra Moraes; Antônio P. Braga; Eduardo M. A. M. Mendes (Biomed. Signal Process. Control., 2020)

Embedded real-time feature extraction for electrode inversion detection in telemedicine electrocardiograms. - 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 (Biomed. Signal Process. Control., 2020)

A Review of Off-Line Mode Dataset Shifts. - Carla Caldeira Takahashi; Antônio P. Braga (IEEE Comput. Intell. Mag., 2020)

Combined weightless neural network FPGA architecture for deforestation surveillance and visual navigation of UAVs. - 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 (Eng. Appl. Artif. Intell., 2020)

Prediction of Mechanical Properties of Seamless Steel Tubes Using Artificial Neural Networks. - Ramon Santos Correa; Patricia Teixeira Sampaio; Rafael Utsch Braga; Victor Alberto Lambertucci; Gustavo Matheus de Almeida; Antônio de Pádua Braga (Int. J. Comput. Intell. Appl., 2020)

A fuzzy data reduction cluster method based on boundary information for large datasets. - Gustavo Rodrigues Lacerda Silva; Paulo Carvalho 002; Luiz C. B. Torres; Antônio P. Braga (Neural Comput. Appl., 2020)

LASSO multi-objective learning algorithm for feature selection. - Frederico Coelho; Marcelo Costa; Michel Verleysen; Antônio P. Braga (Soft Comput., 2020)

Neural Networks Multiobjective Learning With Spherical Representation of Weights. - Honovan P. Rocha; Marcelo Azevedo Costa; Antônio P. Braga (IEEE Trans. Neural Networks Learn. Syst., 2020)

Industrial case study of causal modeling of continuous casting and lamination of steel tubes. - Danilo A. Caldeira Silva; Turíbio Tanus Salis; Antônio de Pádua Braga (LA-CCI, 2021)

Neural Networks Regularization With Graph-Based Local Resampling. - Alex de Assis Santos dos Santos; Luiz C. B. Torres; Lourenço R. G. Araújo; Vítor M. Hanriot; Antônio de Pádua Braga (IEEE Access, 2021)

Online learning of neural networks using random projections and sliding window: A case study of a real industrial process. - 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 (Eng. Appl. Artif. Intell., 2021)

Enhancing Performance of Gabriel Graph-Based Classifiers by a Hardware Co-Processor for Embedded System Applications. - Janier Arias-Garcia; Augusto Mafra; Liliane Gade; Frederico Coelho; Cristiano Leite Castro; Luiz C. B. Torres; Antônio de Pádua Braga (IEEE Trans. Ind. Informatics, 2021)

Guest Editorial: Special Issue on Deep Representation and Transfer Learning for Smart and Connected Health. - Vasile Palade; Stefan Wermter; Ariel Ruiz-Garcia; Antônio de Pádua Braga; Clive Cheong Took (IEEE Trans. Neural Networks Learn. Syst., 2021)

Large Margin Gaussian Mixture Classifier With a Gabriel Graph Geometric Representation of Data Set Structure. - Luiz C. B. Torres; Cristiano Leite Castro; Frederico Coelho; Antônio P. Braga (IEEE Trans. Neural Networks Learn. Syst., 2021)

Time domain graph-based anomaly detection approach applied to a real industrial problem. - Wagner J. Alvarenga; Felipe V. Campos; Alexsander C. A. A. Costa; Turíbio Tanus Salis; Eduardo Magalhães; Luiz C. B. Torres; Antônio P. Braga (Comput. Ind., 2022)

Deep architecture for silica forecasting of a real industrial froth flotation process. - Alexsander C. A. A. Costa; Felipe V. Campos; Lourenço R. G. Araújo; Luiz C. B. Torres; Antônio de Pádua Braga (Eng. Appl. Artif. Intell., 2022)

Multi-objective neural network model selection with a graph-based large margin approach. - Luiz C. B. Torres; Cristiano Leite Castro; Honovan P. Rocha; Gustavo Matheus de Almeida; Antônio P. Braga (Inf. Sci., 2022)

One Class Density Estimation Approach for Fault Detection and Rootcause Analysis in Computer Networks. - 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 (J. Netw. Syst. Manag., 2022)

Cost-Sensitive Learning based on Performance Metric for Imbalanced Data. - Yuri Sousa Aurelio; Gustavo Matheus de Almeida; Cristiano Leite de Castro; Antônio de Pádua Braga (Neural Process. Lett., 2022)

RBF Neural Networks Design with Graph Based Structural Information from Dominating Sets. - Marcelo Queiroz; Frederico Coelho; Luiz C. B. Torres; Felipe V. Campos; Gabriel Lara; Wagner J. Alvarenga; Antônio de Pádua Braga (Neural Process. Lett., 2023)

Learning Kernel Parameters for Support Vector Classification Using Similarity Embeddings. - Antônio de Pádua Braga; Murilo V. F. Menezes; Luiz C. B. Torres (ESANN, 2024)

Distance-based loss function for deep feature space learning of convolutional neural networks. - Eduardo S. Ribeiro; Lourenço R. G. Araújo; Gabriel T. L. Chaves; Antônio P. Braga (Comput. Vis. Image Underst., 2024)

Improved Design for Hardware Implementation of Graph-Based Large Margin Classifiers for Embedded Edge Computing. - Janier Arias-Garcia; Alan Cândido de Souza; Liliane Gade; Jones Yudi Mori; Frederico Coelho; Cristiano Leite Castro; Luiz C. B. Torres; Antônio P. Braga (IEEE Trans. Neural Networks Learn. Syst., 2024)

Hebbian Learning with Kernel-Based Embedding of Input Data. - Thiago A. Ushikoshi; Elias J. R. Freitas; Murilo V. F. Menezes; Wagner J. A. Junior; Luiz C. B. Torres; Antônio de Pádua Braga (Neural Process. Lett., 2024)

Graph-based method for autonomous adaptation in online learning of non-stationary data. - Wagner J. Alvarenga; Alexsander C. A. A. Costa; Felipe V. Campos; Luiz C. B. Torres; Antônio de Pádua Braga (Inf. Sci., 2025)

A projected gradient solution to the minimum connector problem with extensions to support vector machines. - Raul Fonseca Neto; Saulo Moraes Villela; Antônio de Pádua Braga (Pattern Recognit., 2025)

Multiclass Graph-Based Large Margin Classifiers: Unified Approach for Support Vectors and Neural Networks. - Vítor M. Hanriot; Luiz C. B. Torres; Antônio P. Braga (IEEE Trans. Neural Networks Learn. Syst., 2025)