Jacob Montiel
Jacob Montiel
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Zitiert von
Zitiert von
Scikit-multiflow: A multi-output streaming framework
J Montiel, J Read, A Bifet, T Abdessalem
Journal of Machine Learning Research 19 (72), 1-5, 2018
River: machine learning for streaming data in python
J Montiel, M Halford, SM Mastelini, G Bolmier, R Sourty, R Vaysse, ...
Journal of Machine Learning Research 22 (110), 1-8, 2021
Anomaly detection for data streams based on isolation forest using scikit-multiflow
MU Togbe, M Barry, A Boly, Y Chabchoub, R Chiky, J Montiel, VT Tran
Computational Science and Its Applications–ICCSA 2020: 20th International …, 2020
Adaptive XGBoost for Evolving Data Streams
J Montiel, R Mitchell, E Frank, B Pfahringer, T Abdessalem, A Bifet
2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020
C-smote: Continuous synthetic minority oversampling for evolving data streams
A Bernardo, HM Gomes, J Montiel, B Pfahringer, A Bifet, E Della Valle
2020 IEEE International Conference on Big Data (Big Data), 483-492, 2020
Transformers for multi-label classification of medical text: an empirical comparison
V Yogarajan, J Montiel, T Smith, B Pfahringer
International Conference on Artificial Intelligence in Medicine, 114-123, 2021
On ensemble techniques for data stream regression
HM Gomes, J Montiel, SM Mastelini, B Pfahringer, A Bifet
2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020
Seeing the whole patient: using multi-label medical text classification techniques to enhance predictions of medical codes
V Yogarajan, J Montiel, T Smith, B Pfahringer
arXiv preprint arXiv:2004.00430, 2020
Learning fast and slow: A unified batch/stream framework
J Montiel, A Bifet, V Losing, J Read, T Abdessalem
2018 IEEE International Conference on Big Data (Big Data), 1065-1072, 2018
Predicting over-indebtedness on batch and streaming data
J Montiel, A Bifet, T Abdessalem
2017 IEEE International Conference on Big Data (Big Data), 1504-1513, 2017
Evolution-based online automated machine learning
C Kulbach, J Montiel, M Bahri, M Heyden, A Bifet
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 472-484, 2022
StreamMLOps: Operationalizing Online Learning for Big Data Streaming & Real-Time Applications
M Barry, J Montiel, A Bifet, S Wadkar, N Manchev, M Halford, R Chiky, ...
2023 IEEE 39th International Conference on Data Engineering (ICDE), 3508-3521, 2023
Stream2Graph: Dynamic knowledge graph for online learning applied in large-scale network
M Barry, A Bifet, R Chiky, S El Jaouhari, J Montiel, A El Ouafi, E Guerizec
2022 IEEE International Conference on Big Data (Big Data), 2190-2197, 2022
Online clustering: Algorithms, evaluation, metrics, applications and benchmarking
J Montiel, HA Ngo, MH Le-Nguyen, A Bifet
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
Fast and lightweight binary and multi-branch Hoeffding Tree Regressors
SM Mastelini, J Montiel, HM Gomes, A Bifet, B Pfahringer, ...
2021 International Conference on Data Mining Workshops (ICDMW), 380-388, 2021
Challenges of machine learning for data streams in the banking industry
M Barry, A Bifet, R Chiky, J Montiel, VT Tran
Big Data Analytics: 9th International Conference, BDA 2021, Virtual Event …, 2021
Fast and slow machine learning
J Montiel López
Paris Saclay, 2019
Learning from evolving data streams
J Montiel
19th Python in Science Conference, 70-77, 2020
Showcasing the TAIAO project: providing resources for machine learning from images of New Zealand's natural environment
N Lim, A Bifet, D Bull, E Frank, Y Jia, J Montiel, B Pfahringer
Journal of the Royal Society of New Zealand 53 (1), 69-81, 2023
Concatenating BioMed-Transformers to Tackle Long Medical Documents and to Improve the Prediction of Tail-End Labels
V Yogarajan, B Pfahringer, T Smith, J Montiel
International Conference on Artificial Neural Networks, 209-221, 2022
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