SFNClassifier: a scale-free social network method to handle concept drift. - Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck (SAC, 2014)

Applying Ensemble-based Online Learning Techniques on Crime Forecasting. - Anderson José de Souza; André Pinz Borges; Heitor Murilo Gomes; Jean Paul Barddal; Fabrício Enembreck (ICEIS (1), 2015)

Analyzing the Impact of Feature Drifts in Streaming Learning. - Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck (ICONIP (1), 2015)

A Complex Network-Based Anytime Data Stream Clustering Algorithm. - Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck (ICONIP (1), 2015)

On the Discovery of Time Distance Constrained Temporal Association Rules. - Heitor Murilo Gomes; Deborah Ribeiro de Carvalho; Lourdes Zubieta; Jean Paul Barddal; Andreia Malucelli (ICONIP (2), 2015)

A Survey on Feature Drift Adaptation. - Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck (ICTAI, 2015)

SNCStream: a social network-based data stream clustering algorithm. - Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck (SAC, 2015)

Pairwise combination of classifiers for ensemble learning on data streams. - Heitor Murilo Gomes; Jean Paul Barddal; Fabrício Enembreck (SAC, 2015)

Advances on Concept Drift Detection in Regression Tasks Using Social Networks Theory. - Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck (Int. J. Nat. Comput. Res., 2015)

A benchmark of classifiers on feature drifting data streams. - Jean Paul Barddal; Heitor Murilo Gomes; Alceu de Souza Britto Jr.; Fabrício Enembreck (ICPR, 2016)

Overcoming feature drifts via dynamic feature weighted k-nearest neighbor learning. - Jean Paul Barddal; Heitor Murilo Gomes; Jones Granatyr; Alceu de Souza Britto Jr.; Fabrício Enembreck (ICPR, 2016)

Towards emotion-based reputation guessing learning agents. - Jones Granatyr; Jean Paul Barddal; Adriano Weihmayer Almeida; Fabrício Enembreck; Adaiane Pereira dos Santos Granatyr (IJCNN, 2016)

On Dynamic Feature Weighting for Feature Drifting Data Streams. - Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck; Bernhard Pfahringer; Albert Bifet (ECML/PKDD (2), 2016)

SNCStream+: Extending a high quality true anytime data stream clustering algorithm. - Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck; Jean-Paul A. Barthès (Inf. Syst., 2016)

Improving Credit Risk Prediction in Online Peer-to-Peer (P2P) Lending Using Imbalanced Learning Techniques. - Luis Eduardo Boiko Ferreira; Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck (ICTAI, 2017)

A Survey on Ensemble Learning for Data Stream Classification. - Heitor Murilo Gomes; Jean Paul Barddal; Fabrício Enembreck; Albert Bifet (ACM Comput. Surv., 2017)

A survey on feature drift adaptation: Definition, benchmark, challenges and future directions. - Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck; Bernhard Pfahringer (J. Syst. Softw., 2017)

Adaptive random forests for evolving data stream classification. - Heitor Murilo Gomes; Albert Bifet; Jesse Read; Jean Paul Barddal; Fabrício Enembreck; Bernhard Pfahringer; Geoff Holmes 001; Talel Abdessalem (Mach. Learn., 2017)

Adaptive random forests for data stream regression. - Heitor Murilo Gomes; Jean Paul Barddal; Luis Eduardo Boiko Ferreira; Albert Bifet (ESANN, 2018)

An Experimental Perspective on Sampling Methods for Imbalanced Learning From Financial Databases. - Luis Eduardo Boiko Ferreira; Jean Paul Barddal; Fabrício Enembreck; Heitor Murilo Gomes (IJCNN, 2018)

Are fintechs really a hype? A machine learning-based polarity analysis of Brazilian posts on social media. - Marina Ponestke Seara; Andreia Malucelli; Altair Olivo Santin; Jean Paul Barddal (INDIN, 2018)

Iterative subset selection for feature drifting data streams. - Lanqin Yuan; Bernhard Pfahringer; Jean Paul Barddal (SAC, 2018)

Vertical and Horizontal Partitioning in Data Stream Regression Ensembles. - Jean Paul Barddal (IJCNN, 2019)

Learning regularized hoeffding trees from data streams. - Jean Paul Barddal; Fabrício Enembreck (SAC, 2019)

Decision tree-based feature ranking in concept drifting data streams. - Jean Antonio Pereira Karax; Andreia Malucelli; Jean Paul Barddal (SAC, 2019)

Merit-guided dynamic feature selection filter for data streams. - Jean Paul Barddal; Fabrício Enembreck; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer (Expert Syst. Appl., 2019)

Boosting decision stumps for dynamic feature selection on data streams. - Jean Paul Barddal; Fabrício Enembreck; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer (Inf. Syst., 2019)

Correction to: Adaptive random forests for evolving data stream classification. - Heitor Murilo Gomes; Albert Bifet; Jesse Read; Jean Paul Barddal; Fabrício Enembreck; Bernhard Pfahringer; Geoff Holmes 001; Talel Abdessalem (Mach. Learn., 2019)

Machine learning for streaming data: state of the art, challenges, and opportunities. - Heitor Murilo Gomes; Jesse Read; Albert Bifet; Jean Paul Barddal; João Gama 001 (SIGKDD Explor., 2019)

Classifier Pool Generation based on a Two-level Diversity Approach. - Marcos Monteiro; Alceu S. Britto Jr.; Jean Paul Barddal; Luiz S. Oliveira; Robert Sabourin (ICPR, 2020)

An End-to-End Approach for Recognition of Modern and Historical Handwritten Numeral Strings. - Andre G. Hochuli; Alceu S. Britto Jr.; Jean Paul Barddal; Robert Sabourin; Luiz E. S. Oliveira (IJCNN, 2020)

Cost-sensitive learning for imbalanced data streams. - Lucas Loezer; Fabrício Enembreck; Jean Paul Barddal; Alceu de Souza Britto Jr. (SAC, 2020)

Naïve Approaches to Deal With Concept Drifts. - Paulo Ricardo Lisboa de Almeida; Luiz S. Oliveira; Alceu de Souza Britto Jr.; Jean Paul Barddal (SMC, 2020)

Combining Slow and Fast Learning for Improved Credit Scoring. - Jean Paul Barddal; Fabrício Enembreck; Lucas Loezer; Riccardo Lanzuolo (SMC, 2020)

ADADRIFT: An Adaptive Learning Technique for Long-history Stream-based Recommender Systems. - Eduardo Ferreira José; Fabrício Enembreck; Jean Paul Barddal (SMC, 2020)

Improving Multiple Time Series Forecasting with Data Stream Mining Algorithms. - Marcos Alberto Mochinski; Jean Paul Barddal; Fabrício Enembreck (SMC, 2020)

Regularized and incremental decision trees for data streams. - Jean Paul Barddal; Fabrício Enembreck (Ann. des Télécommunications, 2020)

scikit-dyn2sel - A Dynamic Selection Framework for Data Streams. - Lucca Portes Cavalheiro; Jean Paul Barddal; Alceu de Souza Britto Jr.; Laurent Heutte (CoRR, 2020)

Lessons learned from data stream classification applied to credit scoring. - Jean Paul Barddal; Lucas Loezer; Fabrício Enembreck; Riccardo Lanzuolo (Expert Syst. Appl., 2020)

Classifying Potentially Unbounded Hierarchical Data Streams with Incremental Gaussian Naive Bayes. - Eduardo Tieppo; Jean Paul Barddal; Júlio César Nievola (BRACIS (1), 2021)

Interactive Process Drift Detection Framework. - Denise Maria Vecino Sato; Jean Paul Barddal; Edson Emílio Scalabrin (ICAISC (2), 2021)

Towards the Overcome of Performance Pitfalls in Data Stream Mining Tools. - Lucca Portes Cavalheiro; Marco Antonio Zanata Alves; Jean Paul Barddal (IJCNN, 2021)

Dynamically Selected Ensemble for Data Stream Classification. - Lucca Portes Cavalheiro; Alceu de Souza Britto Jr.; Jean Paul Barddal; Laurent Heutte (IJCNN, 2021)

UKIRF: An Item Rejection Framework for Improving Negative Items Sampling in One-Class Collaborative Filtering. - Antônio David Viniski; Jean Paul Barddal; Alceu de Souza Britto Jr. (PAKDD (2), 2021)

Adaptive Global k-Nearest Neighbors for Hierarchical Classification of Data Streams. - Eduardo Tieppo; Jean Paul Barddal; Júlio César Nievola (SMC, 2021)

A case study of batch and incremental recommender systems in supermarket data under concept drifts and cold start. - Antônio David Viniski; Jean Paul Barddal; Alceu de Souza Britto Jr.; Fabrício Enembreck; Humberto Vinicius Aparecido de Campos (Expert Syst. Appl., 2021)

A Machine Learning Approach for School Dropout Prediction in Brazil. - João Gabriel Corrêa Krüger; Jean Paul Barddal; Alceu de Souza Britto Jr. (ESANN, 2022)

Univariate Time Series Prediction using Data Stream Mining Algorithms and Temporal Dependence. - Marcos Alberto Mochinski; Jean Paul Barddal; Fabrício Enembreck (ICAART (2), 2022)

Evaluation of Self-taught Learning-based Representations for Facial Emotion Recognition. - Bruna Rossetto Delazeri; Leonardo León Vera; Jean Paul Barddal; Alessandro L. Koerich; Alceu S. Britto Jr. (IJCNN, 2022)

Assessing Batch and Online Learning for Delivery in Full and On Time Predictions. - Adriano Alves de Lima; Márcie Venâncio Batista; Jean Paul Barddal; Danilo Sipoli Sanches; Luiz Eduardo Soares de Oliveira (IJCNN, 2022)

Classifying Hierarchical Data Streams using Global Classifiers and Summarization Techniques. - Eduardo Tieppo; Jean Paul Barddal; Júlio César Nievola (IJCNN, 2022)

Automatic disease vector mosquitoes identification via hierarchical data stream classification. - Eduardo Tieppo; Jean Paul Barddal; Júlio César Nievola (SAC, 2022)

Pattern Spotting and Image Retrieval in Historical Documents using Deep Hashing. - Caio da S. Dias; Alceu S. Britto Jr.; Jean Paul Barddal; Laurent Heutte; Alessandro L. Koerich (SMC, 2022)

Improving Data Stream Classification using Incremental Yeo-Johnson Power Transformation. - Eduardo Tieppo; Jean Paul Barddal; Júlio César Nievola (SMC, 2022)

Hierarchical classification of data streams: a systematic literature review. - Eduardo Tieppo; Roger Robson dos Santos; Jean Paul Barddal; Júlio César Nievola (Artif. Intell. Rev., 2022)

Evaluating k-NN in the Classification of Data Streams with Concept Drift. - Roberto Souto Maior de Barros; Silas Garrido Teixeira de Carvalho Santos; Jean Paul Barddal (CoRR, 2022)

A Survey on Concept Drift in Process Mining. - Denise Maria Vecino Sato; Sheila Cristiana De Freitas; Jean Paul Barddal; Edson Emílio Scalabrin (ACM Comput. Surv., 2022)

A systematic review on computer vision-based parking lot management applied on public datasets. - Paulo Ricardo Lisboa de Almeida; Jeovane Honório Alves; Rafael Stubs Parpinelli; Jean Paul Barddal (Expert Syst. Appl., 2022)

A Tool for Measuring Energy Consumption in Data Stream Mining. - Eric Kenzo Taniguchi Onuki; Andreia Malucelli; Jean Paul Barddal (BRACIS (3), 2023)

Detecting Relevant Information in High- Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis. - Jeovane Honório Alves; Horácio A. C. G. Pedroso; Rafael Honorio Venetikides; Joel E. M. Köster; Luiz Rodrigo Grochocki; Cinthia O. A. Freitas; Jean Paul Barddal (ICMLA, 2023)

Event-driven Sentiment Drift Analysis in Text Streams: An Application in a Soccer Match. - Cristiano Mesquita Garcia; Alceu de Souza Britto Jr.; Jean Paul Barddal (ICMLA, 2023)

Deep Single Models vs. Ensembles: Insights for a Fast Deployment of Parking Monitoring Systems. - Andre Gustavo Hochuli; Jean Paul Barddal; Gillian Cezar Palhano; Leonardo Matheus Mendes; Paulo Ricardo Lisboa de Almeida (ICMLA, 2023)

Mass-Based Short Term Selection of Classifiers in Data Streams. - Daniel Nowak Assis; Fabrício Enembreck; Jean Paul Barddal (IJCNN, 2023)

Benchmarking Feature Extraction Techniques for Textual Data Stream Classification. - Bruno Siedekum Thuma; Pedro Silva de Vargas; Cristiano Mesquita Garcia; Alceu de Souza Britto Jr.; Jean Paul Barddal (IJCNN, 2023)

Random Forest Dissimilarity for High-Dimension Low Sample Size Classification. - Lucca Portes Cavalheiro; Simon Bernard 001; Jean Paul Barddal; Laurent Heutte (CoRR, 2023)

Concept Drift Adaptation in Text Stream Mining Settings: A Comprehensive Review. - Cristiano Mesquita Garcia; Ramon Simoes Abilio; Alessandro Lameiras Koerich; Alceu de Souza Britto Jr.; Jean Paul Barddal (CoRR, 2023)

Exploring diversity in data complexity and classifier decision spaces for pool generation. - Marcos Monteiro; Alceu de Souza Britto Junior; Jean Paul Barddal; Luiz S. Oliveira; Robert Sabourin (Inf. Fusion, 2023)

Incremental specialized and specialized-generalized matrix factorization models based on adaptive learning rate optimizers. - Antônio David Viniski; Jean Paul Barddal; Alceu de Souza Britto Junior; Humberto Vinicius Aparecido de Campos (Neurocomputing, 2023)

An explainable machine learning approach for student dropout prediction. - João Gabriel Corrêa Krüger; Alceu de Souza Britto Jr.; Jean Paul Barddal (Expert Syst. Appl., 2023)

LongKey: Keyphrase Extraction for Long Documents. - Jeovane Honório Alves; Radu State; Cinthia Obladen de Almendra Freitas; Jean Paul Barddal (IEEE Big Data, 2024)

Is it Fine to Tune? Evaluating SentenceBERT Fine-tuning for Brazilian Portuguese Text Stream Classification. - Bruno Yuiti Leão Imai; Cristiano Mesquita Garcia; Marcio Vinicius Rocha; Alessandro Lameiras Koerich; Alceu de Souza Britto Jr.; Jean Paul Barddal (IEEE Big Data, 2024)

Fuels Demand Forecasting: Identifying Leading Feature Sets, Prediction Strategy, and Regressors. - Jonas Krause; Alexandre C. A. Beiruth; Jean Paul Barddal; Alceu S. Britto Jr.; Vinícius M. A. de Souza (ICMLA, 2024)

Improving Sampling Methods for Fine-Tuning SentenceBERT in Text Streams. - Cristiano Mesquita Garcia; Alessandro Lameiras Koerich; Alceu de Souza Britto Junior; Jean Paul Barddal (ICPR (19), 2024)

Dynamic Modality and View Selection for Emotion Recognition: An Experimental Study on Missing Modality Evaluation. - Luciana Trinkaus Menon; Luiz Carlos Ribeiro Neduziak; Jean Paul Barddal; Alessandro Lameiras Koerich; Alceu de Souza Britto Junior (ICPR (Workshops and Challenges, 4), 2024)

Alleviating Catastrophic Forgetting in Facial Expression Recognition with Emotion-Centered Models. - Israel A. Laurensi R.; Alceu de Souza Britto Jr.; Jean Paul Barddal; Alessandro Lameiras Koerich (ICPR (9), 2024)

Just Change on Change: Adaptive Splitting Time for Decision Trees in Data Stream Classification. - Daniel Nowak Assis; Jean Paul Barddal; Fabrício Enembreck (SAC, 2024)

Adaptive learning on hierarchical data streams using window-weighted Gaussian probabilities. - Eduardo Tieppo; Júlio César Nievola; Jean Paul Barddal (Appl. Soft Comput., 2024)

Methods for Generating Drift in Text Streams. - Cristiano Mesquita Garcia; Alessandro Lameiras Koerich; Alceu de Souza Britto Jr.; Jean Paul Barddal (CoRR, 2024)

Dynamic Modality and View Selection for Multimodal Emotion Recognition with Missing Modalities. - Luciana Trinkaus Menon; Luiz Carlos Ribeiro Neduziak; Jean Paul Barddal; Alessandro Lameiras Koerich; Alceu de Souza Britto Jr. (CoRR, 2024)

Temporal analysis of drifting hashtags in textual data streams: A graph-based application. - Cristiano Mesquita Garcia; Alceu de Souza Britto Jr.; Jean Paul Barddal (Expert Syst. Appl., 2024)

Random forest kernel for high-dimension low sample size classification. - Lucca Portes Cavalheiro; Simon Bernard 001; Jean Paul Barddal; Laurent Heutte (Stat. Comput., 2024)

Representation ensemble learning applied to facial expression recognition. - Bruna Rossetto Delazeri; Andre Gustavo Hochuli; Jean Paul Barddal; Alessandro Lameiras Koerich; Alceu de Souza Britto Jr. (Neural Comput. Appl., 2025)

Concept Drift Adaptation in Text Stream Mining Settings: A Systematic Review. - Cristiano Mesquita Garcia; Ramon Abílio; Alessandro Lameiras Koerich; Alceu de Souza Britto Jr.; Jean Paul Barddal (ACM Trans. Intell. Syst. Technol., 2025)

Behavioral insights of adaptive splitting decision trees in evolving data stream classification. - Daniel Nowak Assis; Jean Paul Barddal; Fabrício Enembreck (Knowl. Inf. Syst., 2025)