SAE: Social Adaptive Ensemble classifier for data streams. - Heitor Murilo Gomes; Fabrício Enembreck (CIDM, 2013)

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

SAE2: advances on the social adaptive ensemble classifier for data streams. - 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)

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)

Advances in network-based ensemble classifiers for evolving data streams: student research abstract. - Heitor Murilo Gomes (SAC, 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)

Feature Scoring using Tree-Based Ensembles for Evolving Data Streams. - Heitor Murilo Gomes; Rodrigo Fernandes de Mello; Bernhard Pfahringer; Albert Bifet (IEEE BigData, 2019)

Semi-supervised Learning over Streaming Data using MOA. - Minh-Huong Le Nguyen; Heitor Murilo Gomes; Albert Bifet (IEEE BigData, 2019)

Streaming Random Patches for Evolving Data Stream Classification. - Heitor Murilo Gomes; Jesse Read; Albert Bifet (ICDM, 2019)

Network of Experts: Learning from Evolving Data Streams Through Network-Based Ensembles. - Heitor Murilo Gomes; Albert Bifet; Philippe Fournier-Viger; Jones Granatyr; Jesse Read (ICONIP (1), 2019)

Adaptive Random Forests with Resampling for Imbalanced data Streams. - Luis Eduardo Boiko Ferreira; Heitor Murilo Gomes; Albert Bifet; Luiz S. Oliveira (IJCNN, 2019)

Inferring Trust Using Personality Aspects Extracted from Texts. - Jones Granatyr; Heitor Murilo Gomes; João Miguel Dias; Ana Maria Paiva; Maria Augusta Silveira Netto Nunes; Edson Emílio Scalabrin; Fábio Spak (SMC, 2019)

Generating action plans for poultry management using artificial neural networks. - Richardson Ribeiro; Dalcimar Casanova; Marcelo Teixeira; André L. Wirth; Heitor Murilo Gomes; André Pinz Borges; Fabrício Enembreck (Comput. Electron. Agric., 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)

C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams. - Alessio Bernardo; Heitor Murilo Gomes; Jacob Montiel; Bernhard Pfahringer; Albert Bifet; Emanuele Della Valle (IEEE BigData, 2020)

Mining Attribute Evolution Rules in Dynamic Attributed Graphs. - Philippe Fournier-Viger; Ganghuan He; Jerry Chun-Wei Lin; Heitor Murilo Gomes (DaWaK, 2020)

Unsupervised Concept Drift Detection Using a Student-Teacher Approach. - Vítor Cerqueira; Heitor Murilo Gomes; Albert Bifet (DS, 2020)

Improving parallel performance of ensemble learners for streaming data through data locality with mini-batching. - Guilherme Weigert Cassales; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer; Hermes Senger (HPCC/DSS/SmartCity, 2020)

Survey on Feature Transformation Techniques for Data Streams. - Maroua Bahri; Albert Bifet; Silviu Maniu; Heitor Murilo Gomes (IJCAI, 2020)

CS-ARF: Compressed Adaptive Random Forests for Evolving Data Stream Classification. - Maroua Bahri; Heitor Murilo Gomes; Albert Bifet; Silviu Maniu (IJCNN, 2020)

On Ensemble Techniques for Data Stream Regression. - Heitor Murilo Gomes; Jacob Montiel; Saulo Martiello Mastelini; Bernhard Pfahringer; Albert Bifet (IJCNN, 2020)

Performance measures for evolving predictions under delayed labelling classification. - Maciej Grzenda; Heitor Murilo Gomes; Albert Bifet (IJCNN, 2020)

An Eager Splitting Strategy for Online Decision Trees. - Chaitanya Manapragada; Heitor Murilo Gomes; Mahsa Salehi; Albert Bifet; Geoffrey I. Webb (CoRR, 2020)

Delayed labelling evaluation for data streams. - Maciej Grzenda; Heitor Murilo Gomes; Albert Bifet (Data Min. Knowl. Discov., 2020)

Combining Static and Dynamic Analysis to Improve Machine Learning-based Malware Classification. - Rajchada Chanajitt; Bernhard Pfahringer; Heitor Murilo Gomes (DSAA, 2021)

Fast and lightweight binary and multi-branch Hoeffding Tree Regressors. - Saulo Martiello Mastelini; Jacob Montiel; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer; André C. P. L. F. de Carvalho (ICDM (Workshops), 2021)

A combined solution for flexible control of poultry houses. - Lucas Schmidt; Dalcimar Casanova; Richardson Ribeiro; Marcelo Teixeira; Heitor Murilo Gomes (Int. J. Comput. Appl. Technol., 2021)

Improving the performance of bagging ensembles for data streams through mini-batching. - Guilherme Weigert Cassales; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer; Hermes Senger (Inf. Sci., 2021)

River: machine learning for streaming data in Python. - Jacob Montiel; Max Halford; Saulo Martiello Mastelini; Geoffrey Bolmier; Raphaël Sourty; Robin Vaysse; Adil Zouitine; Heitor Murilo Gomes; Jesse Read; Talel Abdessalem; Albert Bifet (J. Mach. Learn. Res., 2021)

Learning from evolving data streams through ensembles of random patches. - Heitor Murilo Gomes; Jesse Read; Albert Bifet; Robert J. Durrant (Knowl. Inf. Syst., 2021)

Data stream analysis: Foundations, major tasks and tools. - Maroua Bahri; Albert Bifet; João Gama 001; Heitor Murilo Gomes; Silviu Maniu (WIREs Data Mining Knowl. Discov., 2021)

Multiclass Malware Classification Using Either Static Opcodes or Dynamic API Calls. - Rajchada Chanajitt; Bernhard Pfahringer; Heitor Murilo Gomes; Vithya Yogarajan (AI, 2022)

Adaptive Neural Networks for Online Domain Incremental Continual Learning. - Nuwan Gunasekara; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer (DS, 2022)

A Comparison of Neural Network Architectures for Malware Classification Based on Noriben Operation Sequences. - Rajchada Chanajitt; Bernhard Pfahringer; Heitor Murilo Gomes (ICANN (1), 2022)

Adaptive Online Domain Incremental Continual Learning. - Nuwan Gunasekara; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer (ICANN (1), 2022)

Online Hyperparameter Optimization for Streaming Neural Networks. - Nuwan Gunasekara; Heitor Murilo Gomes; Bernhard Pfahringer; Albert Bifet (IJCNN, 2022)

Balancing the Stability-Plasticity Dilemma with Online Stability Tuning for Continual Learning. - Anton Lee; Heitor Murilo Gomes; Yaqian Zhang (IJCNN, 2022)

A Hybrid Sampling Approach for Imbalanced Binary and Multi-Class Data Using Clustering Analysis. - Abdul Sattar Palli; Jafreezal Jaafar; Manzoor Ahmed Hashmani; Heitor Murilo Gomes; Abdul Rehman Gilal (IEEE Access, 2022)

Fast & Furious: Modelling Malware Detection as Evolving Data Streams. - Fabrício Ceschin; Marcus Botacin; Heitor Murilo Gomes; Felipe Azevedo Pinage; Luiz S. Oliveira; André Grégio (CoRR, 2022)

An eager splitting strategy for online decision trees in ensembles. - Chaitanya Manapragada; Heitor Murilo Gomes; Mahsa Salehi; Albert Bifet; Geoffrey I. Webb (Data Min. Knowl. Discov., 2022)

SOKNL: A novel way of integrating K-nearest neighbours with adaptive random forest regression for data streams. - Yibin Sun; Bernhard Pfahringer; Heitor Murilo Gomes; Albert Bifet (Data Min. Knowl. Discov., 2022)

Resource-Aware Edge-Based Stream Analytics. - Ioan Petri; Ioan Chirila; Heitor Murilo Gomes; Albert Bifet; Omer F. Rana (IEEE Internet Comput., 2022)

LP-ROBIN: Link prediction in dynamic networks exploiting incremental node embedding. - Emanuele Pio Barracchia; Gianvito Pio; Albert Bifet; Heitor Murilo Gomes; Bernhard Pfahringer; Michelangelo Ceci (Inf. Sci., 2022)

Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning. - Anton Lee; Yaqian Zhang; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer (CIKM, 2023)

Survey on Online Streaming Continual Learning. - Nuwan Gunasekara; Bernhard Pfahringer; Heitor Murilo Gomes; Albert Bifet (IJCAI, 2023)

A Survey on Semi-supervised Learning for Delayed Partially Labelled Data Streams. - Heitor Murilo Gomes; Maciej Grzenda; Rodrigo Fernandes de Mello; Jesse Read; Minh-Huong Le Nguyen; Albert Bifet (ACM Comput. Surv., 2023)

Fast & Furious: On the modelling of malware detection as an evolving data stream. - Fabrício Ceschin; Marcus Botacin; Heitor Murilo Gomes; Felipe Azevedo Pinage; Luiz S. Oliveira; André Grégio (Expert Syst. Appl., 2023)

Balancing Performance and Energy Consumption of Bagging Ensembles for the Classification of Data Streams in Edge Computing. - Guilherme Weigert Cassales; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer; Hermes Senger (IEEE Trans. Netw. Serv. Manag., 2023)

STUDD: a student-teacher method for unsupervised concept drift detection. - Vítor Cerqueira; Heitor Murilo Gomes; Albert Bifet; Luís Torgo (Mach. Learn., 2023)

Mini-batching with Fused Training and Testing for Data Streams Processing on the Edge. - Reginaldo Luna; Guilherme Weigert Cassales; Bernhard Pfahringer; Albert Bifet; Heitor Murilo Gomes; Hermes Senger (CF, 2024)

Recurrent Concept Drifts on Data Streams. - Nuwan Gunasekara; Bernhard Pfahringer; Heitor Murilo Gomes; Albert Bifet; Yun Sing Koh (IJCAI, 2024)

Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme. - Yun Sing Koh; Albert Bifet; Karin R. Bryan; Guilherme Weigert Cassales; Olivier Graffeuille; Nick Jin Sean Lim; Phil Mourot; Ding Ning; Bernhard Pfahringer; Varvara Vetrova; Heitor Murilo Gomes (IJCAI, 2024)

Practical Machine Learning for Streaming Data. - Heitor Murilo Gomes; Albert Bifet (KDD, 2024)

Adaptive Prediction Interval for Data Stream Regression. - Yibin Sun; Bernhard Pfahringer; Heitor Murilo Gomes; Albert Bifet (PAKDD (3), 2024)

Leveraging Plasticity in Incremental Decision Trees. - Marco Heyden; Heitor Murilo Gomes; Edouard Fouché; Bernhard Pfahringer; Klemens Böhm (ECML/PKDD (5), 2024)

Real-Time Energy Pricing in New Zealand: An Evolving Stream Analysis. - Yibin Sun; Heitor Murilo Gomes; Bernhard Pfahringer; Albert Bifet (PRICAI (5), 2024)

Cross-Regional Malware Detection via Model Distilling and Federated Learning. - Marcus Botacin; Heitor Murilo Gomes (RAID, 2024)

Machine Learning (In) Security: A Stream of Problems. - Fabrício Ceschin; Marcus Botacin; Albert Bifet; Bernhard Pfahringer; Luiz S. Oliveira; Heitor Murilo Gomes; André Grégio (DTRAP, 2024)

SeGDroid: An Android malware detection method based on sensitive function call graph learning. - Zhen Liu 017; Ruoyu Wang 002; Nathalie Japkowicz; Heitor Murilo Gomes; Bitao Peng; Wenbin Zhang 002 (Expert Syst. Appl., 2024)

Gradient boosted trees for evolving data streams. - Nuwan Gunasekara; Bernhard Pfahringer; Heitor Murilo Gomes; Albert Bifet (Mach. Learn., 2024)

Kolmogorov-Arnold Networks Still Catastrophically Forget but Differently from MLP. - Anton Lee; Heitor Murilo Gomes; Yaqian Zhang; W. Bastiaan Kleijn (AAAI, 2025)

Towards Explainable Drift Detection and Early Retrain in ML-Based Malware Detection Pipelines. - Jayesh Tripathi; Heitor Murilo Gomes; Marcus Botacin (DIMVA (2), 2025)

Towards more realistic evaluations: The impact of label delays in malware detection pipelines. - Marcus Botacin; Heitor Murilo Gomes (Comput. Secur., 2025)

CLOFAI: A Dataset of Real And Fake Image Classification Tasks for Continual Learning. - William Doherty; Anton Lee; Heitor Murilo Gomes (CoRR, 2025)

A Semi-Supervised Active Learning Neural Network for Data Streams With Concept Drift. - Botao Jiao; Heitor Murilo Gomes; Bing Xue 001; Yinan Guo 001; Mengjie Zhang 001 (IEEE Comput. Intell. Mag., 2025)

Evaluation for Regression Analyses on Evolving Data Streams. - Yibin Sun; Heitor Murilo Gomes; Bernhard Pfahringer; Albert Bifet (CoRR, 2025)

CapyMOA: Efficient Machine Learning for Data Streams in Python. - Heitor Murilo Gomes; Anton Lee; Nuwan Gunasekara; Yibin Sun; Guilherme Weigert Cassales; Justin Liu; Marco Heyden; Vítor Cerqueira; Maroua Bahri; Yun Sing Koh; Bernhard Pfahringer; Albert Bifet (CoRR, 2025)