César Lincoln C. Mattos

According to our database, César Lincoln C. Mattos authored at least 42 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Spatio-temporal wind speed forecasting with approximate Bayesian uncertainty quantification.

Airton F. Souza Neto, César L. C. Mattos, João P. P. Gomes

Neural Comput. Appl., October, 2024

Edge AI for Internet of Medical Things: A literature review.

Atslands Rego da Rocha, Matheus Monteiro, César L. C. Mattos, Madson L. D. Dias, Jorge Soares, Regis Pires Magalhães, José A. F. de Macêdo

Comput. Electr. Eng., 2024

Bayesian ART for incomplete datasets.

Alan L. S. Matias, João Paulo Pordeus Gomes, César Lincoln C. Mattos, Ajalmar R. da Rocha Neto, Diego Mesquita

Appl. Soft Comput., 2024

Amortized Variational Deep Kernel Learning.

Alan L. S. Matias, César Lincoln C. Mattos, João Paulo Pordeus Gomes, Diego Mesquita

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Minimal Learning Machine for Multi-Label Learning.

Joonas Hämäläinen, Amauri H. de Souza, César L. C. Mattos, João P. P. Gomes, Tommi Kärkkäinen

CoRR, 2023

Thin and deep Gaussian processes.

Daniel Augusto de Souza, Alexander Nikitin, St John, Magnus Ross, Mauricio A. Álvarez, Marc Peter Deisenroth, João Paulo Pordeus Gomes, Diego Mesquita, César Lincoln C. Mattos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

CVEjoin: An Information Security Vulnerability and Threat Intelligence Dataset.

Francisco R. P. da Ponte, Emanuel B. Rodrigues, César L. C. Mattos

Proceedings of the Advanced Information Networking and Applications, 2023

A Vulnerability Risk Assessment Methodology Using Active Learning.

Francisco R. P. da Ponte, Emanuel B. Rodrigues, César L. C. Mattos

Proceedings of the Advanced Information Networking and Applications, 2023

2022

Bayesian Multilateration.

Alisson S. C. Alencar, César L. C. Mattos, João P. P. Gomes, Diego Mesquita

IEEE Signal Process. Lett., 2022

Evaluating Link Lifetime Prediction to Support Computational Offloading Decision in VANETs.

Paulo Rocha, Alisson Barbosa de Souza, Gilvan Maia, César L. C. Mattos, Francisco Airton Silva, Paulo A. L. Rego, Tuan Anh Nguyen, Jae-Woo Lee

Sensors, 2022

Self-tuning portfolio-based Bayesian optimization.

Thiago de P. Vasconcelos, Daniel Augusto R. M. A. de Souza, Gustavo C. de M. Virgolino, César L. C. Mattos, João P. P. Gomes

Expert Syst. Appl., 2022

The role of bug report evolution in reliable fixing estimation.

Renan Gomes Vieira, César Lincoln C. Mattos, Lincoln S. Rocha, João Paulo Pordeus Gomes, Matheus Paixão

Empir. Softw. Eng., 2022

A Text Classification Methodology to Assist a Large Technical Support System.

Elene Firmeza Ohata, César Lincoln Cavalcante Mattos, Samuel Luz Gomes, Elizângela de S. Rebouças, Paulo Antonio Leal Rego

IEEE Access, 2022

Bayesian Analysis of Bug-Fixing Time using Report Data.

Renan Gomes Vieira, Diego Mesquita, César Lincoln C. Mattos, Ricardo Britto, Lincoln S. Rocha, João Gomes

Proceedings of the ESEM '22: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement, Helsinki, Finland, September 19, 2022

2021

A novel fuzzy ARTMAP with area of influence.

Alan L. S. Matias, Ajalmar R. da Rocha Neto, César Lincoln C. Mattos, João Paulo Pordeus Gomes

Neurocomputing, 2021

A Practical Guide to Support Predictive Tasks in Data Science.

José Augusto Câmara Filho, José Maria Monteiro, César Lincoln C. Mattos, Juvêncio Santos Nobre

Proceedings of the 23rd International Conference on Enterprise Information Systems, 2021

FakeWhastApp.BR: NLP and Machine Learning Techniques for Misinformation Detection in Brazilian Portuguese WhatsApp Messages.

Lucas Cabral, José Maria Monteiro, José Wellington Franco da Silva, César Lincoln C. Mattos, Pedro Jorge Chaves Mourão

Proceedings of the 23rd International Conference on Enterprise Information Systems, 2021

Learning GPLVM with arbitrary kernels using the unscented transformation.

Daniel Augusto de Souza, Diego P. P. Mesquita, João Paulo Pordeus Gomes, César Lincoln C. Mattos

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

LS-SVR as a Bayesian RBF Network.

Diego P. P. Mesquita, Luis A. Freitas, João P. P. Gomes, César L. C. Mattos

IEEE Trans. Neural Networks Learn. Syst., 2020

A sparse linear regression model for incomplete datasets.

Marcelo B. A. Veras, Diego P. P. Mesquita, César Lincoln C. Mattos, João P. P. Gomes

Pattern Anal. Appl., 2020

Detectando Doença de Parkinson - Uma Comparação de Modelos de Aprendizagem de Máquina com Redução de Dimensionalidade Diferencialmente Privada.

Manuel Edvar Bento Filho, Maria de Lourdes Maia Silva, Patrícia Vieira da Silva Barros, César Lincoln Cavalcante Mattos, Javam de Castro Machado

Proceedings of the 35th Brazilian Symposium on Databases, 2020

An Optimized Approach to Huntington's Disease Detecting via Audio Signals Processing with Dimensionality Reduction.

Matheus T. Guimarães, Aldísio Gonçalves Medeiros, Jefferson S. Almeida, Marcos Falcão y Martin, Robertas Damasevicius, Rytis Maskeliunas, César Lincoln Cavalcante Mattos, Pedro Pedrosa Rebouças Filho

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Anomaly Detection in Trajectory Data with Normalizing Flows.

Madson L. D. Dias, César Lincoln C. Mattos, Ticiana L. Coelho da Silva, José Antônio Fernandes de Macêdo, Wellington C. P. Silva

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

A New Methodology for Classifying QRS Morphology in ECG Signals.

Weslley L. Caldas, João Paulo do Vale Madeiro, César Lincoln C. Mattos, João Paulo Pordeus Gomes

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

On the Use of Cultural Enhancement Strategies to Improve the NEAT Algorithm.

Arthur L. A. Paulino, Yuri Lenon Barbosa Nogueira, João P. P. Gomes, César L. C. Mattos, Leonardo Ramos Rodrigues

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019

A stochastic variational framework for Recurrent Gaussian Processes models.

César Lincoln C. Mattos, Guilherme A. Barreto

Neural Networks, 2019

Minimal Learning Machine: Theoretical Results and Clustering-Based Reference Point Selection.

Joonas Hämäläinen, Alisson S. C. Alencar, Tommi Kärkkäinen, César L. C. Mattos, Amauri H. Souza Júnior, João P. P. Gomes

CoRR, 2019

Unscented Gaussian Process Latent Variable Model: learning from uncertain inputs with intractable kernels.

Daniel Augusto R. M. A. de Souza, César Lincoln C. Mattos, João Paulo Pordeus Gomes

CoRR, 2019

OnMLM: An Online Formulation for the Minimal Learning Machine.

Alan L. S. Matias, César L. C. Mattos, Tommi Kärkkäinen, João P. P. Gomes, Ajalmar R. da Rocha Neto

Proceedings of the Advances in Computational Intelligence, 2019

No-PASt-BO: Normalized Portfolio Allocation Strategy for Bayesian Optimization.

Thiago de P. Vasconcelos, Daniel Augusto R. M. A. de Souza, César L. C. Mattos, João P. P. Gomes

Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019

Sparse minimal learning machine using a diversity measure minimization.

Madson Luiz Dantas Dias, Lucas Silva de Sousa, Ajalmar R. da Rocha Neto, César L. C. Mattos, João P. P. Gomes, Tommi Kärkkäinen

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Evaluation of Data Based Normal Behavior Models for Fault Detection in Wind Turbines.

Daniel Souza, Thiago de P. Vasconcelos, César L. C. Mattos, João Gomes

Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

Audio Plugin Recommendation Systems for Music Production.

Paulo Mateus Moura da Silva, César Lincoln Cavalcante Mattos, Amauri Holanda de Souza Júnior

Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

2017

Metaheuristic optimization for automatic clustering of customer-oriented supply chain data.

César Lincoln C. Mattos, Guilherme A. Barreto, Dennis Horstkemper, Bernd Hellingrath

Proceedings of the 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, 2017

Randomized Neural Networks for Recursive System Identification in the Presence of Outliers: A Performance Comparison.

César Lincoln C. Mattos, Guilherme A. Barreto, Gonzalo Acuña

Proceedings of the Advances in Computational Intelligence, 2017

2016

Recurrent Gaussian Processes.

César Lincoln C. Mattos, Zhenwen Dai, Andreas C. Damianou, Jeremy Forth, Guilherme A. Barreto, Neil D. Lawrence

Proceedings of the 4th International Conference on Learning Representations, 2016

2015

Performance Evaluation of Least Squares SVR in Robust Dynamical System Identification.

José Daniel A. Santos, César Lincoln C. Mattos, Guilherme A. Barreto

Proceedings of the Advances in Computational Intelligence, 2015

An Empirical Evaluation of Robust Gaussian Process Models for System Identification.

César Lincoln C. Mattos, José Daniel A. Santos, Guilherme A. Barreto

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2015, 2015

2014

An improved hybrid particle swarm optimization algorithm applied to economic modeling of radio resource allocation.

César Lincoln C. Mattos, Guilherme A. Barreto, Francisco Rodrigo P. Cavalcanti

Electron. Commer. Res., 2014

A Novel Recursive Kernel-Based Algorithm for Robust Pattern Classification.

José Daniel A. Santos, César Lincoln C. Mattos, Guilherme De A. Barreto

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2014, 2014

Improved Adaline Networks for Robust Pattern Classification.

César Lincoln C. Mattos, José Daniel A. Santos, Guilherme A. Barreto

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

2013

ARTIE and MUSCLE models: building ensemble classifiers from fuzzy ART and SOM networks.

César Lincoln C. Mattos, Guilherme A. Barreto

Neural Comput. Appl., 2013