Predicting over-indebtedness on batch and streaming data. - Jacob Montiel; Albert Bifet; Talel Abdessalem (IEEE BigData, 2017)

Learning Fast and Slow: A Unified Batch/Stream Framework. - Jacob Montiel; Albert Bifet; Viktor Losing; Jesse Read; Talel Abdessalem (IEEE BigData, 2018)

Scalable Model-Based Cascaded Imputation of Missing Data. - Jacob Montiel; Jesse Read; Albert Bifet; Talel Abdessalem (PAKDD (3), 2018)

Scikit-Multiflow: A Multi-output Streaming Framework. - Jacob Montiel; Jesse Read; Albert Bifet; Talel Abdessalem (J. Mach. Learn. Res., 2018)

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)

Anomaly Detection for Data Streams Based on Isolation Forest Using Scikit-Multiflow. - Maurras Ulbricht Togbe; Mariam Barry; Aliou Boly; Yousra Chabchoub; Raja Chiky; Jacob Montiel; Vinh-Thuy Tran (ICCSA (4), 2020)

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

Adaptive XGBoost for Evolving Data Streams. - Jacob Montiel; Rory Mitchell; Eibe Frank; Bernhard Pfahringer; Talel Abdessalem; Albert Bifet (IJCNN, 2020)

Learning from evolving data streams. - Jacob Montiel (SciPy, 2020)

Seeing The Whole Patient: Using Multi-Label Medical Text Classification Techniques to Enhance Predictions of Medical Codes. - Vithya Yogarajan; Jacob Montiel; Tony Smith; Bernhard Pfahringer (CoRR, 2020)

Transformers for Multi-label Classification of Medical Text: An Empirical Comparison. - Vithya Yogarajan; Jacob Montiel; Tony Smith; Bernhard Pfahringer (AIME, 2021)

Challenges of Machine Learning for Data Streams in the Banking Industry. - Mariam Barry; Albert Bifet; Raja Chiky; Jacob Montiel; Vinh-Thuy Tran (BDA, 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)

Improving Predictions of Tail-end Labels using Concatenated BioMed-Transformers for Long Medical Documents. - Vithya Yogarajan; Bernhard Pfahringer; Tony Smith; Jacob Montiel (CoRR, 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)

Predicting COVID-19 Patient Shielding: A Comprehensive Study. - Vithya Yogarajan; Jacob Montiel; Tony Smith; Bernhard Pfahringer (AI, 2022)

Stream2Graph: Dynamic Knowledge Graph for Online Learning Applied in Large-scale Network. - Mariam Barry; Albert Bifet; Raja Chiky; Saad El Jaouhari; Jacob Montiel; Aissa El Ouafi; Eric Guerizec (IEEE Big Data, 2022)

StreamFlow: A System for Summarizing and Learning Over Industrial Big Data Streams. - Mariam Barry; Saad El Jaouhari; Albert Bifet; Jacob Montiel; Eric Guerizec; Raja Chiky (IEEE Big Data, 2022)

Concatenating BioMed-Transformers to Tackle Long Medical Documents and to Improve the Prediction of Tail-End Labels. - Vithya Yogarajan; Bernhard Pfahringer; Tony Smith; Jacob Montiel (ICANN (2), 2022)

Online Clustering: Algorithms, Evaluation, Metrics, Applications and Benchmarking. - Jacob Montiel; Hoang-Anh Ngo; Minh-Huong Le Nguyen; Albert Bifet (KDD, 2022)

Evolution-Based Online Automated Machine Learning. - Cedric Kulbach; Jacob Montiel; Maroua Bahri; Marco Heyden; Albert Bifet (PAKDD (1), 2022)

StreamMLOps: Operationalizing Online Learning for Big Data Streaming & Real-Time Applications. - Mariam Barry; Jacob Montiel; Albert Bifet; Sameer Wadkar; Nikolay Manchev; Max Halford; Raja Chiky; Saad El Jaouhari; Katherine B. Shakman; Joudi Al Fehaily; Fabrice Le Deit; Vinh-Thuy Tran; et al. (ICDE, 2023)