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2020 – today
- 2024
[j21]Eduardo Tieppo
, Júlio César Nievola, Jean Paul Barddal:
Adaptive learning on hierarchical data streams using window-weighted Gaussian probabilities. Appl. Soft Comput. 152: 111271 (2024)- [j20]Cristiano Mesquita Garcia, Alceu de Souza Britto Jr., Jean Paul Barddal:
Temporal analysis of drifting hashtags in textual data streams: A graph-based application. Expert Syst. Appl. 257: 125007 (2024) - [j19]Lucca Portes Cavalheiro, Simon Bernard, Jean Paul Barddal, Laurent Heutte:
Random forest kernel for high-dimension low sample size classification. Stat. Comput. 34(1): 9 (2024) - [c48]Daniel Nowak Assis, Jean Paul Barddal, Fabrício Enembreck:
Just Change on Change: Adaptive Splitting Time for Decision Trees in Data Stream Classification. SAC 2024: 351-357 - [i18]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 abs/2402.10230 (2024) - [i17]Cristiano Mesquita Garcia, Alessandro Lameiras Koerich, Alceu de Souza Britto Jr., Jean Paul Barddal:
Methods for Generating Drift in Text Streams. CoRR abs/2403.12328 (2024) - [i16]Cristiano Mesquita Garcia, Alessandro Lameiras Koerich, Alceu de Souza Britto Jr., Jean Paul Barddal:
Improving Sampling Methods for Fine-tuning SentenceBERT in Text Streams. CoRR abs/2403.15455 (2024) - [i15]Luciana Trinkaus Menon, Luiz Carlos Ribeiro Neduziak, Jean Paul Barddal, Alessandro Lameiras Koerich, Alceu de Souza Britto Jr:
Dynamic Modality and View Selection for Multimodal Emotion Recognition with Missing Modalities. CoRR abs/2404.12251 (2024) - [i14]Israel A. Laurensi R., Alceu de Souza Britto Jr., Jean Paul Barddal, Alessandro Lameiras Koerich:
Alleviating Catastrophic Forgetting in Facial Expression Recognition with Emotion-Centered Models. CoRR abs/2404.12260 (2024) - 2023
- [j18]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: 120933 (2023) - [j17]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: 126515 (2023) - [j16]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: 567-587 (2023) - [c47]Eric Kenzo Taniguchi Onuki, Andreia Malucelli, Jean Paul Barddal:
A Tool for Measuring Energy Consumption in Data Stream Mining. BRACIS (3) 2023: 429-440 - [c46]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. ICMLA 2023: 1379-1384 - [c45]Cristiano Mesquita Garcia, Alceu de Souza Britto Jr., Jean Paul Barddal:
Event-driven Sentiment Drift Analysis in Text Streams: An Application in a Soccer Match. ICMLA 2023: 1920-1927 - [c44]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:
Detecting Relevant Information in High- Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis. ICMLA 2023: 1979-1985 - [c43]Daniel Nowak Assis, Fabrício Enembreck, Jean Paul Barddal:
Mass-Based Short Term Selection of Classifiers in Data Streams. IJCNN 2023: 1-8 - [c42]Bruno Siedekum Thuma, Pedro Silva de Vargas, Cristiano Mesquita Garcia, Alceu de Souza Britto Jr., Jean Paul Barddal:
Benchmarking Feature Extraction Techniques for Textual Data Stream Classification. IJCNN 2023: 1-8 - [i13]Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck:
Advances on Concept Drift Detection in Regression Tasks using Social Networks Theory. CoRR abs/2304.09788 (2023) - [i12]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 abs/2309.16495 (2023) - [i11]Lucca Portes Cavalheiro, Simon Bernard, Jean Paul Barddal, Laurent Heutte:
Random Forest Dissimilarity for High-Dimension Low Sample Size Classification. CoRR abs/2310.14710 (2023) - [i10]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 abs/2311.04905 (2023) - [i9]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 abs/2312.02901 (2023) - 2022
- [j15]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): 3243-3282 (2022) - [j14]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): 189:1-189:38 (2022) - [j13]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: 116731 (2022) - [c41]João Gabriel Corrêa Krüger, Jean Paul Barddal, Alceu de Souza Britto Jr.:
A Machine Learning Approach for School Dropout Prediction in Brazil. ESANN 2022 - [c40]Marcos Alberto Mochinski, Jean Paul Barddal, Fabrício Enembreck:
Univariate Time Series Prediction using Data Stream Mining Algorithms and Temporal Dependence. ICAART (2) 2022: 398-408 - [c39]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: 1-8 - [c38]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: 1-9 - [c37]Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola:
Classifying Hierarchical Data Streams using Global Classifiers and Summarization Techniques. IJCNN 2022: 1-8 - [c36]Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola:
Automatic disease vector mosquitoes identification via hierarchical data stream classification. SAC 2022: 1005-1012 - [c35]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: 2869-2875 - [c34]Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola:
Improving Data Stream Classification using Incremental Yeo-Johnson Power Transformation. SMC 2022: 3286-3292 - [i8]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 abs/2203.06463 (2022) - [i7]Bruna Rossetto Delazeri, Leonardo León Vera, Alceu S. Britto Jr., Jean Paul Barddal, Alessandro L. Koerich:
Evaluation of Self-taught Learning-based Representations for Facial Emotion Recognition. CoRR abs/2204.12624 (2022) - [i6]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 abs/2208.02397 (2022) - [i5]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 abs/2210.03119 (2022) - 2021
- [j12]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: 114890 (2021) - [c33]Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola:
Classifying Potentially Unbounded Hierarchical Data Streams with Incremental Gaussian Naive Bayes. BRACIS (1) 2021: 421-436 - [c32]Denise Maria Vecino Sato, Jean Paul Barddal, Edson Emílio Scalabrin:
Interactive Process Drift Detection Framework. ICAISC (2) 2021: 192-204 - [c31]Lucca Portes Cavalheiro, Marco Antonio Zanata Alves, Jean Paul Barddal:
Towards the Overcome of Performance Pitfalls in Data Stream Mining Tools. IJCNN 2021: 1-6 - [c30]Lucca Portes Cavalheiro, Alceu de Souza Britto Jr., Jean Paul Barddal, Laurent Heutte:
Dynamically Selected Ensemble for Data Stream Classification. IJCNN 2021: 1-7 - [c29]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: 549-560 - [c28]Eduardo Tieppo, Jean Paul Barddal, Júlio César Nievola:
Adaptive Global k-Nearest Neighbors for Hierarchical Classification of Data Streams. SMC 2021: 631-636 - [i4]Denise Maria Vecino Sato, Sheila Cristiana De Freitas, Jean Paul Barddal, Edson Emílio Scalabrin:
A Survey on Concept Drift in Process Mining. CoRR abs/2112.02000 (2021) - 2020
- [j11]Jean Paul Barddal, Fabrício Enembreck:
Regularized and incremental decision trees for data streams. Ann. des Télécommunications 75(9-10): 493-503 (2020) - [j10]Jean Paul Barddal, Lucas Loezer, Fabrício Enembreck, Riccardo Lanzuolo:
Lessons learned from data stream classification applied to credit scoring. Expert Syst. Appl. 162: 113899 (2020) - [c27]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: 2414-2421 - [c26]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: 1-8 - [c25]Lucas Loezer, Fabrício Enembreck, Jean Paul Barddal, Alceu de Souza Britto Jr.:
Cost-sensitive learning for imbalanced data streams. SAC 2020: 498-504 - [c24]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: 1052-1059 - [c23]Marcos Alberto Mochinski, Jean Paul Barddal, Fabrício Enembreck:
Improving Multiple Time Series Forecasting with Data Stream Mining Algorithms. SMC 2020: 1060-1067 - [c22]Jean Paul Barddal, Fabrício Enembreck, Lucas Loezer, Riccardo Lanzuolo:
Combining Slow and Fast Learning for Improved Credit Scoring. SMC 2020: 1149-1154 - [c21]Eduardo Ferreira José, Fabrício Enembreck, Jean Paul Barddal:
ADADRIFT: An Adaptive Learning Technique for Long-history Stream-based Recommender Systems. SMC 2020: 2593-2600 - [i3]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 abs/2004.03337 (2020) - [i2]Lucca Portes Cavalheiro, Jean Paul Barddal, Alceu de Souza Britto Jr., Laurent Heutte:
scikit-dyn2sel - A Dynamic Selection Framework for Data Streams. CoRR abs/2008.08920 (2020) - [i1]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 abs/2011.01908 (2020)
2010 – 2019
- 2019
- [j9]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: 227-242 (2019) - [j8]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: 13-29 (2019) - [j7]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): 1877-1878 (2019) - [j6]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): 6-22 (2019) - [c20]Jean Paul Barddal:
Vertical and Horizontal Partitioning in Data Stream Regression Ensembles. IJCNN 2019: 1-8 - [c19]Jean Paul Barddal, Fabrício Enembreck:
Learning regularized hoeffding trees from data streams. SAC 2019: 574-581 - [c18]Jean Antonio Pereira Karax, Andreia Malucelli, Jean Paul Barddal:
Decision tree-based feature ranking in concept drifting data streams. SAC 2019: 590-592 - 2018
- [c17]Heitor Murilo Gomes, Jean Paul Barddal, Luis Eduardo Boiko Ferreira, Albert Bifet:
Adaptive random forests for data stream regression. ESANN 2018 - [c16]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: 1-6 - [c15]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: 233-238 - [c14]Lanqin Yuan, Bernhard Pfahringer, Jean Paul Barddal:
Iterative subset selection for feature drifting data streams. SAC 2018: 510-517 - 2017
- [j5]Heitor Murilo Gomes, Jean Paul Barddal, Fabrício Enembreck, Albert Bifet:
A Survey on Ensemble Learning for Data Stream Classification. ACM Comput. Surv. 50(2): 23:1-23:36 (2017) - [j4]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: 278-294 (2017) - [j3]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): 1469-1495 (2017) - [c13]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: 175-181 - 2016
- [j2]Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck, Jean-Paul A. Barthès:
SNCStream+: Extending a high quality true anytime data stream clustering algorithm. Inf. Syst. 62: 60-73 (2016) - [c12]Jean Paul Barddal, Heitor Murilo Gomes, Alceu de Souza Britto Jr., Fabrício Enembreck:
A benchmark of classifiers on feature drifting data streams. ICPR 2016: 2180-2185 - [c11]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: 2186-2191 - [c10]Jones Granatyr, Jean Paul Barddal, Adriano Weihmayer Almeida, Fabrício Enembreck, Adaiane Pereira dos Santos Granatyr:
Towards emotion-based reputation guessing learning agents. IJCNN 2016: 3801-3808 - [c9]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: 129-144 - 2015
- [j1]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): 26-41 (2015) - [c8]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: 17-24 - [c7]Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck:
Analyzing the Impact of Feature Drifts in Streaming Learning. ICONIP (1) 2015: 21-28 - [c6]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: 510-519 - [c5]Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck:
A Complex Network-Based Anytime Data Stream Clustering Algorithm. ICONIP (1) 2015: 615-622 - [c4]Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck:
A Survey on Feature Drift Adaptation. ICTAI 2015: 1053-1060 - [c3]Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck:
SNCStream: a social network-based data stream clustering algorithm. SAC 2015: 935-940 - [c2]Heitor Murilo Gomes, Jean Paul Barddal, Fabrício Enembreck:
Pairwise combination of classifiers for ensemble learning on data streams. SAC 2015: 941-946 - 2014
- [c1]Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck:
SFNClassifier: a scale-free social network method to handle concept drift. SAC 2014: 786-791
Coauthor Index
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