Jean Paul Barddal

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 76

Top Topics

Stream Clustering

Top Venues

Publications

Lucca Portes Cavalheiro, Simon Bernard, Jean Paul Barddal, Laurent Heutte
Random forest kernel for high-dimension low sample size classification. Stat. Comput. 34 (1) (2024)
Cristiano Mesquita Garcia, Alceu de Souza Britto Jr., Jean Paul Barddal
Temporal Analysis of Drifting Hashtags in Textual Data Streams: A Graph-Based Application. CoRR (2024)
Daniel Nowak Assis, Fabrício Enembreck, Jean Paul Barddal
Mass-Based Short Term Selection of Classifiers in Data Streams. IJCNN (2023)
Lucca Portes Cavalheiro, Simon Bernard, Jean Paul Barddal, Laurent Heutte
Random Forest Dissimilarity for High-Dimension Low Sample Size Classification. CoRR (2023)
Bruno Siedekum Thuma, Pedro Silva de Vargas, Cristiano Garcia, Alceu de Souza Britto Jr., Jean Paul Barddal
Benchmarking Feature Extraction Techniques for Textual Data Stream Classification. IJCNN (2023)
Antônio David Viniski, Jean Paul Barddal, Alceu de Souza Britto Junior, Humberto Vinicius Aparecido de Campos
Incremental specialized and specialized-generalized matrix factorization models based on adaptive learning rate optimizers. Neurocomputing 552 (2023)
Marcos Monteiro, Alceu de Souza Britto Junior, Jean Paul Barddal, Luiz S. Oliveira, Robert Sabourin
Exploring diversity in data complexity and classifier decision spaces for pool generation. Inf. Fusion 89 (2023)
Eric Kenzo Taniguchi Onuki, Andreia Malucelli, Jean Paul Barddal
A Tool for Measuring Energy Consumption in Data Stream Mining. BRACIS (3) (2023)
Andre Gustavo Hochuli, Jean Paul Barddal, Gillian Cezar Palhano, Leonardo Matheus Mendes, Paulo Ricardo Lisboa de Almeida
Deep Single Models vs. Ensembles: Insights for a Fast Deployment of Parking Monitoring Systems. CoRR (2023)
Jeovane Honório Alves, Horácio A. C. G. Pedroso, Rafael Honorio Venetikides, Joel E. M. Köster, Luiz Rodrigo Grochocki, Cinthia O. de A. Freitas, Jean Paul Barddal
Detecting Relevant Information in High-Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis. CoRR (2023)
Cristiano Mesquita Garcia, Ramon Simoes Abilio, Alessandro Lameiras Koerich, Alceu de Souza Britto Jr., Jean Paul Barddal
Concept Drift Adaptation in Text Stream Mining Settings: A Comprehensive Review. CoRR (2023)
João Gabriel Corrêa Krüger, Alceu de Souza Britto Jr., Jean Paul Barddal
An explainable machine learning approach for student dropout prediction. Expert Syst. Appl. 233 (2023)
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck
Advances on Concept Drift Detection in Regression Tasks using Social Networks Theory. CoRR (2023)
Roberto Souto Maior de Barros, Silas Garrido Teixeira de Carvalho Santos, Jean Paul Barddal
Evaluating k-NN in the Classification of Data Streams with Concept Drift. CoRR (2022)
Caio da S. Dias, Alceu S. Britto Jr., Jean Paul Barddal, Laurent Heutte, Alessandro L. Koerich
Pattern Spotting and Image Retrieval in Historical Documents using Deep Hashing. SMC (2022)
Bruna Delazeri, Leonardo L. Veras, Alceu S. Britto Jr., Jean Paul Barddal, Alessandro L. Koerich
Evaluation of Self-taught Learning-based Representations for Facial Emotion Recognition. CoRR (2022)
Bruna Rossetto Delazeri, Leonardo León Vera, Jean Paul Barddal, Alessandro L. Koerich, Alceu S. Britto Jr.
Evaluation of Self-taught Learning-based Representations for Facial Emotion Recognition. IJCNN (2022)
Denise Maria Vecino Sato, Sheila Cristiana De Freitas, Jean Paul Barddal, Edson Emílio Scalabrin
A Survey on Concept Drift in Process Mining. ACM Comput. Surv. 54 (9) (2022)
Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola
Improving Data Stream Classification using Incremental Yeo-Johnson Power Transformation. SMC (2022)
Caio da S. Dias, Alceu de Souza Britto Jr., Jean Paul Barddal, Laurent Heutte, Alessandro L. Koerich
Pattern Spotting and Image Retrieval in Historical Documents using Deep Hashing. CoRR (2022)
Paulo Ricardo Lisboa de Almeida, Jeovane Honório Alves, Rafael Stubs Parpinelli, Jean Paul Barddal
A Systematic Review on Computer Vision-Based Parking Lot Management Applied on Public Datasets. CoRR (2022)
Eduardo Tieppo, Roger Robson dos Santos, Jean Paul Barddal, Júlio César Nievola
Hierarchical classification of data streams: a systematic literature review. Artif. Intell. Rev. 55 (4) (2022)
Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola
Automatic disease vector mosquitoes identification via hierarchical data stream classification. SAC (2022)
Marcos Alberto Mochinski, Jean Paul Barddal, Fabrício Enembreck
Univariate Time Series Prediction using Data Stream Mining Algorithms and Temporal Dependence. ICAART (2) (2022)
João Gabriel Corrêa Krüger, Jean Paul Barddal, Alceu de Souza Britto Jr.
A Machine Learning Approach for School Dropout Prediction in Brazil. ESANN (2022)
Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola
Classifying Hierarchical Data Streams using Global Classifiers and Summarization Techniques. IJCNN (2022)
Paulo Ricardo Lisboa de Almeida, Jeovane Honório Alves, Rafael Stubs Parpinelli, Jean Paul Barddal
A systematic review on computer vision-based parking lot management applied on public datasets. Expert Syst. Appl. 198 (2022)
Adriano Alves de Lima, Márcie Venâncio Batista, Jean Paul Barddal, Danilo Sipoli Sanches, Luiz Eduardo Soares de Oliveira
Assessing Batch and Online Learning for Delivery in Full and On Time Predictions. IJCNN (2022)
Lucca Portes Cavalheiro, Alceu de Souza Britto Jr., Jean Paul Barddal, Laurent Heutte
Dynamically Selected Ensemble for Data Stream Classification. IJCNN (2021)
Antônio David Viniski, Jean Paul Barddal, Alceu de Souza Britto Jr.
UKIRF: An Item Rejection Framework for Improving Negative Items Sampling in One-Class Collaborative Filtering. PAKDD (2) (2021)
Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola
Adaptive Global k-Nearest Neighbors for Hierarchical Classification of Data Streams. SMC (2021)
Antônio David Viniski, Jean Paul Barddal, Alceu de Souza Britto Jr., Fabrício Enembreck, Humberto Vinicius Aparecido de Campos
A case study of batch and incremental recommender systems in supermarket data under concept drifts and cold start. Expert Syst. Appl. 176 (2021)
Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola
Classifying Potentially Unbounded Hierarchical Data Streams with Incremental Gaussian Naive Bayes. BRACIS (1) (2021)
Denise Maria Vecino Sato, Jean Paul Barddal, Edson Emílio Scalabrin
Interactive Process Drift Detection Framework. ICAISC (2) (2021)
Lucca Portes Cavalheiro, Marco Antonio Zanata Alves, Jean Paul Barddal
Towards the Overcome of Performance Pitfalls in Data Stream Mining Tools. IJCNN (2021)
Denise Maria Vecino Sato, Sheila Cristiana De Freitas, Jean Paul Barddal, Edson Emílio Scalabrin
A Survey on Concept Drift in Process Mining. CoRR (2021)
Jean Paul Barddal, Lucas Loezer, Fabrício Enembreck, Riccardo Lanzuolo
Lessons learned from data stream classification applied to credit scoring. Expert Syst. Appl. 162 (2020)
Jean Paul Barddal, Fabrício Enembreck, Lucas Loezer, Riccardo Lanzuolo
Combining Slow and Fast Learning for Improved Credit Scoring. SMC (2020)
Marcos Monteiro, Alceu S. Britto Jr., Jean Paul Barddal, Luiz S. Oliveira, Robert Sabourin
Classifier Pool Generation based on a Two-level Diversity Approach. ICPR (2020)
Marcos Monteiro, Alceu S. Britto Jr., Jean Paul Barddal, Luiz S. Oliveira, Robert Sabourin
Classifier Pool Generation based on a Two-level Diversity Approach. CoRR (2020)
Lucas Loezer, Fabrício Enembreck, Jean Paul Barddal, Alceu de Souza Britto Jr.
Cost-sensitive learning for imbalanced data streams. SAC (2020)
Andre G. Hochuli, Alceu S. Britto Jr., Jean Paul Barddal, Robert Sabourin, Luiz E. S. Oliveira
An End-to-End Approach for Recognition of Modern and Historical Handwritten Numeral Strings. IJCNN (2020)
Lucca Portes Cavalheiro, Jean Paul Barddal, Alceu de Souza Britto Jr., Laurent Heutte
scikit-dyn2sel - A Dynamic Selection Framework for Data Streams. CoRR (2020)
Andre G. Hochuli, Alceu S. Britto Jr., Jean Paul Barddal, Luiz E. S. Oliveira, Robert Sabourin
An End-to-End Approach for Recognition of Modern and Historical Handwritten Numeral Strings. CoRR (2020)
Eduardo Ferreira José, Fabrício Enembreck, Jean Paul Barddal
ADADRIFT: An Adaptive Learning Technique for Long-history Stream-based Recommender Systems. SMC (2020)
Paulo Ricardo Lisboa de Almeida, Luiz S. Oliveira, Alceu de Souza Britto Jr., Jean Paul Barddal
Naïve Approaches to Deal With Concept Drifts. SMC (2020)
Jean Paul Barddal, Fabrício Enembreck
Regularized and incremental decision trees for data streams. Ann. des Télécommunications 75 (9-10) (2020)
Marcos Alberto Mochinski, Jean Paul Barddal, Fabrício Enembreck
Improving Multiple Time Series Forecasting with Data Stream Mining Algorithms. SMC (2020)
Heitor Murilo Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem
Correction to: Adaptive random forests for evolving data stream classification. Mach. Learn. 108 (10) (2019)
Jean Antonio Pereira Karax, Andreia Malucelli, Jean Paul Barddal
Decision tree-based feature ranking in concept drifting data streams. SAC (2019)
Jean Paul Barddal, Fabrício Enembreck, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer
Merit-guided dynamic feature selection filter for data streams. Expert Syst. Appl. 116 (2019)
Heitor Murilo Gomes, Jesse Read, Albert Bifet, Jean Paul Barddal, João Gama
Machine learning for streaming data: state of the art, challenges, and opportunities. SIGKDD Explor. 21 (2) (2019)
Jean Paul Barddal
Vertical and Horizontal Partitioning in Data Stream Regression Ensembles. IJCNN (2019)
Jean Paul Barddal, Fabrício Enembreck, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer
Boosting decision stumps for dynamic feature selection on data streams. Inf. Syst. 83 (2019)
Jean Paul Barddal, Fabrício Enembreck
Learning regularized hoeffding trees from data streams. SAC (2019)
Lanqin Yuan, Bernhard Pfahringer, Jean Paul Barddal
Iterative subset selection for feature drifting data streams. SAC (2018)
Luis Eduardo Boiko Ferreira, Jean Paul Barddal, Fabrício Enembreck, Heitor Murilo Gomes
An Experimental Perspective on Sampling Methods for Imbalanced Learning From Financial Databases. IJCNN (2018)
Marina Ponestke Seara, Andreia Malucelli, Altair Olivo Santin, Jean Paul Barddal
Are fintechs really a hype? A machine learning-based polarity analysis of Brazilian posts on social media. INDIN (2018)
Heitor Murilo Gomes, Jean Paul Barddal, Luis Eduardo Boiko Ferreira, Albert Bifet
Adaptive random forests for data stream regression. ESANN (2018)
Luis Eduardo Boiko Ferreira, Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck
Improving Credit Risk Prediction in Online Peer-to-Peer (P2P) Lending Using Imbalanced Learning Techniques. ICTAI (2017)
Heitor Murilo Gomes, Jean Paul Barddal, Fabrício Enembreck, Albert Bifet
A Survey on Ensemble Learning for Data Stream Classification. ACM Comput. Surv. 50 (2) (2017)
Heitor Murilo Gomes, Albert Bifet, Jesse Read, Jean Paul Barddal, Fabrício Enembreck, Bernhard Pfahringer, Geoff Holmes, Talel Abdessalem
Adaptive random forests for evolving data stream classification. Mach. Learn. 106 (9-10) (2017)
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck, Bernhard Pfahringer
A survey on feature drift adaptation: Definition, benchmark, challenges and future directions. J. Syst. Softw. 127 (2017)
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck, Jean-Paul A. Barthès
: Extending a high quality true anytime data stream clustering algorithm. Inf. Syst. 62 (2016)
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck, Bernhard Pfahringer, Albert Bifet
On Dynamic Feature Weighting for Feature Drifting Data Streams. ECML/PKDD (2) (2016)
Jean Paul Barddal, Heitor Murilo Gomes, Alceu de Souza Britto Jr., Fabrício Enembreck
A benchmark of classifiers on feature drifting data streams. ICPR (2016)
Jones Granatyr, Jean Paul Barddal, Adriano Weihmayer Almeida, Fabrício Enembreck, Adaiane Pereira dos Santos Granatyr
Towards emotion-based reputation guessing learning agents. IJCNN (2016)
Jean Paul Barddal, Heitor Murilo Gomes, Jones Granatyr, Alceu de Souza Britto Jr., Fabrício Enembreck
Overcoming feature drifts via dynamic feature weighted k-nearest neighbor learning. ICPR (2016)
Anderson José de Souza, André Pinz Borges, Heitor Murilo Gomes, Jean Paul Barddal, Fabrício Enembreck
Applying Ensemble-based Online Learning Techniques on Crime Forecasting. ICEIS (1) (2015)
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck
Analyzing the Impact of Feature Drifts in Streaming Learning. ICONIP (1) (2015)
Heitor Murilo Gomes, Jean Paul Barddal, Fabrício Enembreck
Pairwise combination of classifiers for ensemble learning on data streams. SAC (2015)
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck
SNCStream: a social network-based data stream clustering algorithm. SAC (2015)
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck
Advances on Concept Drift Detection in Regression Tasks Using Social Networks Theory. Int. J. Nat. Comput. Res. 5 (1) (2015)
Heitor Murilo Gomes, Deborah Ribeiro de Carvalho, Lourdes Zubieta, Jean Paul Barddal, Andreia Malucelli
On the Discovery of Time Distance Constrained Temporal Association Rules. ICONIP (2) (2015)
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck
A Complex Network-Based Anytime Data Stream Clustering Algorithm. ICONIP (1) (2015)
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck
A Survey on Feature Drift Adaptation. ICTAI (2015)
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck
SFNClassifier: a scale-free social network method to handle concept drift. SAC (2014)