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Journal Articles
- 2022
[j10]Elene Firmeza Ohata
, César Lincoln Cavalcante Mattos, Samuel Luz Gomes, Elizângela de S. Rebouças, Paulo Antonio Leal Rego:
A Text Classification Methodology to Assist a Large Technical Support System. IEEE Access 10: 108413-108421 (2022)- [j9]Renan Gomes Vieira, César Lincoln C. Mattos, Lincoln S. Rocha, João Paulo Pordeus Gomes, Matheus Paixão:
The role of bug report evolution in reliable fixing estimation. Empir. Softw. Eng. 27(7): 164 (2022) - [j8]Thiago de P. Vasconcelos, Daniel Augusto R. M. A. de Souza, Gustavo C. de M. Virgolino, César L. C. Mattos, João P. P. Gomes:
Self-tuning portfolio-based Bayesian optimization. Expert Syst. Appl. 188: 115847 (2022) - [j7]Alisson S. C. Alencar, César L. C. Mattos, João P. P. Gomes, Diego Mesquita:
Bayesian Multilateration. IEEE Signal Process. Lett. 29: 962-966 (2022) - 2021
- [j6]Alan L. S. Matias, Ajalmar R. da Rocha Neto, César Lincoln C. Mattos, João Paulo Pordeus Gomes:
A novel fuzzy ARTMAP with area of influence. Neurocomputing 432: 80-90 (2021) - 2020
- [j5]Marcelo B. A. Veras, Diego P. P. Mesquita, César Lincoln C. Mattos, João P. P. Gomes:
A sparse linear regression model for incomplete datasets. Pattern Anal. Appl. 23(3): 1293-1303 (2020) - [j4]Diego P. P. Mesquita, Luis A. Freitas, João P. P. Gomes, César L. C. Mattos:
LS-SVR as a Bayesian RBF Network. IEEE Trans. Neural Networks Learn. Syst. 31(10): 4389-4393 (2020) - 2019
- [j3]César Lincoln C. Mattos, Guilherme A. Barreto:
A stochastic variational framework for Recurrent Gaussian Processes models. Neural Networks 112: 54-72 (2019) - 2014
- [j2]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
- [j1]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)
Conference and Workshop Papers
- 2023
- [c23]Francisco R. P. da Ponte, Emanuel B. Rodrigues, César L. C. Mattos:
A Vulnerability Risk Assessment Methodology Using Active Learning. AINA (2) 2023: 171-182 - [c22]Francisco R. P. da Ponte, Emanuel B. Rodrigues, César L. C. Mattos:
CVEjoin: An Information Security Vulnerability and Threat Intelligence Dataset. AINA (1) 2023: 380-392 - 2022
- [c21]Renan Gomes Vieira, Diego Mesquita, César Lincoln C. Mattos, Ricardo Britto, Lincoln S. Rocha, João Gomes:
Bayesian Analysis of Bug-Fixing Time using Report Data. ESEM 2022: 57-68 - 2021
- [c20]Daniel Augusto de Souza, Diego P. P. Mesquita, João Paulo Pordeus Gomes, César Lincoln C. Mattos:
Learning GPLVM with arbitrary kernels using the unscented transformation. AISTATS 2021: 451-459 - [c19]Lucas Cabral, José Maria Monteiro, José Wellington Franco da Silva, César Lincoln C. Mattos, Pedro Jorge Chaves Mourão:
FakeWhastApp.BR: NLP and Machine Learning Techniques for Misinformation Detection in Brazilian Portuguese WhatsApp Messages. ICEIS (1) 2021: 63-74 - [c18]José Augusto Câmara Filho, José Maria Monteiro, César Lincoln C. Mattos, Juvêncio Santos Nobre:
A Practical Guide to Support Predictive Tasks in Data Science. ICEIS (1) 2021: 248-255 - 2020
- [c17]Arthur L. A. Paulino, Yuri Lenon Barbosa Nogueira, João P. P. Gomes, César L. C. Mattos, Leonardo Ramos Rodrigues:
On the Use of Cultural Enhancement Strategies to Improve the NEAT Algorithm. CEC 2020: 1-8 - [c16]Weslley L. Caldas, João Paulo do Vale Madeiro, César Lincoln C. Mattos, João Paulo Pordeus Gomes:
A New Methodology for Classifying QRS Morphology in ECG Signals. IJCNN 2020: 1-9 - [c15]Madson L. D. Dias, César Lincoln C. Mattos, Ticiana L. Coelho da Silva, José Antônio Fernandes de Macêdo, Wellington C. P. Silva:
Anomaly Detection in Trajectory Data with Normalizing Flows. IJCNN 2020: 1-8 - [c14]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:
An Optimized Approach to Huntington's Disease Detecting via Audio Signals Processing with Dimensionality Reduction. IJCNN 2020: 1-8 - [c13]Manuel Edvar Bento Filho, Maria de Lourdes Maia Silva, Patrícia Vieira da Silva Barros, César Lincoln Cavalcante Mattos, Javam de Castro Machado:
Detectando Doença de Parkinson - Uma Comparação de Modelos de Aprendizagem de Máquina com Redução de Dimensionalidade Diferencialmente Privada. SBBD 2020: 253-258 - 2019
- [c12]Paulo Mateus Moura da Silva, César Lincoln Cavalcante Mattos, Amauri Holanda de Souza Júnior:
Audio Plugin Recommendation Systems for Music Production. BRACIS 2019: 854-859 - [c11]Daniel Souza, Thiago de P. Vasconcelos, César L. C. Mattos, João Gomes:
Evaluation of Data Based Normal Behavior Models for Fault Detection in Wind Turbines. BRACIS 2019: 878-883 - [c10]Madson Luiz Dantas Dias, Lucas Silva de Sousa, Ajalmar R. da Rocha Neto, César L. C. Mattos, João P. P. Gomes, Tommi Kärkkäinen:
Sparse minimal learning machine using a diversity measure minimization. ESANN 2019 - [c9]Thiago de P. Vasconcelos, Daniel Augusto R. M. A. de Souza, César L. C. Mattos, João P. P. Gomes:
No-PASt-BO: Normalized Portfolio Allocation Strategy for Bayesian Optimization. ICTAI 2019: 561-568 - [c8]Alan L. S. Matias, César L. C. Mattos, Tommi Kärkkäinen, João P. P. Gomes, Ajalmar R. da Rocha Neto:
OnMLM: An Online Formulation for the Minimal Learning Machine. IWANN (1) 2019: 557-568 - 2017
- [c7]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 - [c6]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
- [c5]César Lincoln C. Mattos, Zhenwen Dai, Andreas C. Damianou, Jeremy Forth, Guilherme A. Barreto, Neil D. Lawrence:
Recurrent Gaussian Processes. ICLR (Poster) 2016 - 2015
- [c4]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 - [c3]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
- [c2]César Lincoln C. Mattos, José Daniel A. Santos, Guilherme A. Barreto:
Improved Adaline Networks for Robust Pattern Classification. ICANN 2014: 579-586 - [c1]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
Informal and Other Publications
- 2023
- [i7]Joonas Hämäläinen, Amauri H. de Souza, César L. C. Mattos, João P. P. Gomes, Tommi Kärkkäinen:
Minimal Learning Machine for Multi-Label Learning. CoRR abs/2305.05518 (2023) - [i6]Daniel Augusto de Souza, Alexander Nikitin, St John, Magnus Ross, Mauricio A. Álvarez, Marc Peter Deisenroth, João P. P. Gomes, Diego Mesquita, César Lincoln C. Mattos:
Thin and Deep Gaussian Processes. CoRR abs/2310.11527 (2023) - 2020
- [i5]Madson Luiz Dantas Dias, César Lincoln C. Mattos, Ticiana L. Coelho da Silva, José Antônio Fernandes de Macêdo, Wellington C. P. Silva:
Anomaly Detection in Trajectory Data with Normalizing Flows. CoRR abs/2004.05958 (2020) - 2019
- [i4]Diego P. P. Mesquita, Luis A. Freitas, João P. P. Gomes, César L. C. Mattos:
LS-SVR as a Bayesian RBF network. CoRR abs/1905.00332 (2019) - [i3]Daniel Augusto R. M. A. de Souza, César Lincoln C. Mattos, João Paulo Pordeus Gomes:
Unscented Gaussian Process Latent Variable Model: learning from uncertain inputs with intractable kernels. CoRR abs/1907.01867 (2019) - [i2]Thiago de P. Vasconcelos, Daniel Augusto R. M. A. de Souza, César L. C. Mattos, João P. P. Gomes:
No-PASt-BO: Normalized Portfolio Allocation Strategy for Bayesian Optimization. CoRR abs/1908.00361 (2019) - [i1]Joonas Hämäläinen, Alisson S. C. Alencar, Tommi Kärkkäinen, César L. C. Mattos, Amauri H. Souza Júnior, João P. P. Gomes:
Minimal Learning Machine: Theoretical Results and Clustering-Based Reference Point Selection. CoRR abs/1909.09978 (2019)
Coauthor Index
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