Daniel F. Leite

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 37

Top Topics

Incremental Learning

Top Venues

IEEE Trans. Fuzzy Syst.

Publications

Daniel F. Leite, Arnab Sharma, Caglar Demir, Axel-Cyrille Ngonga Ngomo
Interpretability Index Based on Balanced Volumes for Transparent Models and Agnostic Explainers. FUZZ (2024)
Arnab Sharma, Daniel F. Leite, Caglar Demir, Axel-Cyrille Ngonga Ngomo
Trading-Off Interpretability and Accuracy in Medical Applications: A Study Toward Optimal Explainability of Hoeffding Trees. FUZZ (2024)
Daniel F. Leite, Alisson Silva, Gabriella Casalino, Arnab Sharma, Danielle Fortunato, Axel-Cyrille Ngonga Ngomo
EGNN-C+: Interpretable Evolving Granular Neural Network and Application in Classification of Weakly-Supervised EEG Data Streams. EAIS (2024)
Daniel F. Leite, Fernando A. C. Gomide
Data Driven Fuzzy and Neural Dynamic Systems Modeling. ICMLC (2023)
Daniel F. Leite, Igor Skrjanc, Saso Blazic, Andrej Zdesar, Fernando A. C. Gomide
Interval incremental learning of interval data streams and application to vehicle tracking. Inf. Sci. 630 (2023)
Daniel F. Leite, Fernando A. C. Gomide, Ronald R. Yager
Data Driven Fuzzy Modeling Using Level Sets. FUZZ-IEEE (2022)
Leticia Decker, Daniel F. Leite, Francesco Minarini, Simone Rossi Tisbeni, Daniele Bonacorsi
Unsupervised Learning and Online Anomaly Detection: An On-Condition Log-Based Maintenance System. Int. J. Embed. Real Time Commun. Syst. 13 (1) (2022)
Leticia Decker, Daniel F. Leite, Daniele Bonacorsi
Explainable Log Parsing and Online Interval Granular Classification from Streams of Words. FUZZ-IEEE (2022)
Daniel F. Leite, Volnei Frigeri Jr., Rodrigo Medeiros
Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games. LA-CCI (2021)
Daniel F. Leite, Volnei Frigeri Jr., Rodrigo Medeiros
Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games. CoRR (2021)
Charles Aguiar, Daniel F. Leite, Daniel Pereira, Goran Andonovski, Igor Skrjanc
Nonlinear modeling and robust LMI fuzzy control of overhead crane systems. J. Frankl. Inst. 358 (2) (2021)
Daniel F. Leite, Pedro Henrique Silva Coutinho, Iury Bessa, Murilo C. O. Camargos Filho, Luiz Cordovil Junior, Reinaldo M. Palhares
Incremental Learning and State-Space Evolving Fuzzy Control of Nonlinear Time-Varying Systems with Unknown Model. CoRR (2021)
Charles Aguiar, Daniel F. Leite
Unsupervised Fuzzy eIX: Evolving Internal-eXternal Fuzzy Clustering. CoRR (2020)
Leticia Decker, Daniel F. Leite, Luca Giommi, Daniele Bonacorsi
Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach. FUZZ-IEEE (2020)
Daniel F. Leite, Goran Andonovski, Igor Skrjanc, Fernando A. C. Gomide
Optimal Rule-Based Granular Systems From Data Streams. IEEE Trans. Fuzzy Syst. 28 (3) (2020)
Charles Aguiar, Daniel F. Leite
Unsupervised Fuzzy eIX: Evolving Internal-eXternal Fuzzy Clustering. EAIS (2020)
Fabricio P. Lucas, Pyramo Costa, Rose Batalha, Daniel F. Leite, Igor Skrjanc
Fault detection in smart grids with time-varying distributed generation using wavelet energy and evolving neural networks. Evol. Syst. 11 (2) (2020)
Sergio Silva, Pyramo Costa, Marcio Santana, Daniel F. Leite
Evolving neuro-fuzzy network for real-time high impedance fault detection and classification. Neural Comput. Appl. 32 (12) (2020)
Daniel F. Leite, Igor Skrjanc, Fernando A. C. Gomide
An overview on evolving systems and learning from stream data. Evol. Syst. 11 (2) (2020)
Leticia Decker, Daniel F. Leite, Luca Giommi, Daniele Bonacorsi
Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach. CoRR (2020)
Leticia Decker, Daniel F. Leite, Fabio Viola, Daniele Bonacorsi
Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers. EAIS (2020)
Daniel F. Leite, Leticia Decker, Marcio Santana, Paulo Vitor de Campos Souza
EGFC: Evolving Gaussian Fuzzy Classifier from Never-Ending Semi-Supervised Data Streams - With Application to Power Quality Disturbance Detection and Classification. CoRR (2020)
Leticia Decker, Daniel F. Leite, Fabio Viola, Daniele Bonacorsi
Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers. CoRR (2020)
Daniel F. Leite, Leticia Decker, Marcio Santana, Paulo Vitor de Campos Souza
EGFC: Evolving Gaussian Fuzzy Classifier from Never-Ending Semi-Supervised Data Streams - With Application to Power Quality Disturbance Detection and Classification. FUZZ-IEEE (2020)
Cristiano Garcia, Daniel F. Leite, Igor Skrjanc
Incremental Missing-Data Imputation for Evolving Fuzzy Granular Prediction. IEEE Trans. Fuzzy Syst. 28 (10) (2020)
Daniel F. Leite, Fernando A. C. Gomide, Igor Skrjanc
Multiobjective Optimization of Fully Autonomous Evolving Fuzzy Granular Models. FUZZ-IEEE (2019)
Daniel F. Leite, Charles Aguiar, Daniel Pereira, Gustavo Souza, Igor Skrjanc
Nonlinear Fuzzy State-Space Modeling and LMI Fuzzy Control of Overhead Cranes. FUZZ-IEEE (2019)
Daniel F. Leite, Igor Skrjanc
Ensemble of evolving optimal granular experts, OWA aggregation, and time series prediction. Inf. Sci. 504 (2019)
Cristiano Garcia, Ahmed Esmin, Daniel F. Leite, Igor Skrjanc
Evolvable fuzzy systems from data streams with missing values: With application to temporal pattern recognition and cryptocurrency prediction. Pattern Recognit. Lett. 128 (2019)
Igor Skrjanc, José Antonio Iglesias, Araceli Sanchis, Daniel F. Leite, Edwin Lughofer, Fernando A. C. Gomide
Evolving fuzzy and neuro-fuzzy approaches in clustering, regression, identification, and classification: A Survey. Inf. Sci. 490 (2019)
Fabricio P. Lucas, Pyramo Costa, Rose Batalha, Daniel F. Leite
High Impedance Fault Detection in Time-Varying Distributed Generation Systems Using Adaptive Neural Networks. IJCNN (2018)
Eduardo A. Soares, Pyramo Costa, Bruno Costa, Daniel F. Leite
Ensemble of evolving data clouds and fuzzy models for weather time series prediction. Appl. Soft Comput. 64 (2018)
Eduardo A. Soares, Heloisa A. Camargo, Suzana J. Camargo, Daniel F. Leite
Incremental Gaussian Granular Fuzzy Modeling Applied to Hurricane Track Forecasting. FUZZ-IEEE (2018)
Vania C. Mota, Flavio A. Damasceno, Daniel F. Leite
Fuzzy clustering and fuzzy validity measures for knowledge discovery and decision making in agricultural engineering. Comput. Electron. Agric. 150 (2018)
Vania C. Mota, Flavio A. Damasceno, Eduardo A. Soares, Daniel F. Leite
Fuzzy clustering methods applied to the evaluation of compost bedded pack barns. FUZZ-IEEE (2017)
Eduardo A. Soares, Vania C. Mota, Ricardo Poucas, Daniel F. Leite
Cloud-based evolving intelligent method for weather time series prediction. FUZZ-IEEE (2017)
Daniel F. Leite, Marcio Santana, Ana Borges, Fernando A. C. Gomide
Fuzzy Granular Neural Network for incremental modeling of nonlinear chaotic systems. FUZZ-IEEE (2016)
Lourenco Bueno, Pyramo Costa, Israel Mendes, Enderson Cruz, Daniel F. Leite
Evolving ensemble of fuzzy models for multivariate time series prediction. FUZZ-IEEE (2015)
Daniel F. Leite, Reinaldo M. Palhares, Víctor C. S. Campos, Fernando A. C. Gomide
Evolving Granular Fuzzy Model-Based Control of Nonlinear Dynamic Systems. IEEE Trans. Fuzzy Syst. 23 (4) (2015)
Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide
Evolving granular neural networks from fuzzy data streams. Neural Networks 38 (2013)
Daniel F. Leite, Rosangela Ballini, Pyramo Costa Jr., Fernando A. C. Gomide
Evolving fuzzy granular modeling from nonstationary fuzzy data streams. Evol. Syst. 3 (2) (2012)
Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide
Evolving granular neural network for fuzzy time series forecasting. IJCNN (2012)
André Paim Lemos, Daniel F. Leite, Leandro Maciel, Rosangela Ballini, Walmir M. Caminhas, Fernando A. C. Gomide
Evolving fuzzy linear regression tree approach for forecasting sales volume of petroleum products. FUZZ-IEEE (2012)
Daniel F. Leite, Fernando A. C. Gomide, Rosangela Ballini, Pyramo Costa Jr.
Fuzzy granular evolving modeling for time series prediction. FUZZ-IEEE (2011)
Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide
Granular Approach for Evolving System Modeling. IPMU (2010)
Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide
Evolving granular neural network for semi-supervised data stream classification. IJCNN (2010)
Daniel F. Leite, Pyramo Costa Jr., Fernando A. C. Gomide
Evolving granular classification neural networks. IJCNN (2009)