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Heitor Murilo Gomes
Heitor Murilo Gomes
Zweryfikowany adres z vuw.ac.nz - Strona główna
Tytuł
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Cytowane przez
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Adaptive random forests for evolving data stream classification
HM Gomes, A Bifet, J Read, JP Barddal, F Enembreck, B Pfharinger, ...
Machine Learning 106, 1469-1495, 2017
6972017
A survey on ensemble learning for data stream classification
HM Gomes, JP Barddal, F Enembreck, A Bifet
ACM Computing Surveys (CSUR) 50 (2), 1-36, 2017
5882017
Machine learning for streaming data: state of the art, challenges, and opportunities
HM Gomes, J Read, A Bifet, JP Barddal, J Gama
ACM SIGKDD Explorations Newsletter 21 (2), 6-22, 2019
2532019
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
2082021
A survey on feature drift adaptation: Definition, benchmark, challenges and future directions
JP Barddal, HM Gomes, F Enembreck, B Pfahringer
Journal of Systems and Software 127, 278-294, 2017
1162017
Streaming random patches for evolving data stream classification
HM Gomes, J Read, A Bifet
2019 IEEE international conference on data mining (ICDM), 240-249, 2019
1152019
Data stream analysis: Foundations, major tasks and tools
M Bahri, A Bifet, J Gama, HM Gomes, S Maniu
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, e1405, 2021
962021
Adaptive random forests for data stream regression.
HM Gomes, JP Barddal, LEB Ferreira, A Bifet
ESANN, 2018
632018
Shallow security: On the creation of adversarial variants to evade machine learning-based malware detectors
F Ceschin, M Botacin, HM Gomes, LS Oliveira, A Grégio
Proceedings of the 3rd Reversing and Offensive-oriented Trends Symposium, 1-9, 2019
472019
Adaptive random forests with resampling for imbalanced data streams
LEB Ferreira, HM Gomes, A Bifet, LS Oliveira
2019 International Joint Conference on Neural Networks (IJCNN), 1-6, 2019
442019
On dynamic feature weighting for feature drifting data streams
JP Barddal, H Murilo Gomes, F Enembreck, B Pfahringer, A Bifet
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016
442016
J. a. Gama,“
HM Gomes, J Read, A Bifet, JP Barddal
Machine learning for streaming data: State of the art, challenges, and …, 2019
392019
Delayed labelling evaluation for data streams
M Grzenda, HM Gomes, A Bifet
Data Mining and Knowledge Discovery 34 (5), 1237-1266, 2020
372020
Boosting decision stumps for dynamic feature selection on data streams
JP Barddal, F Enembreck, HM Gomes, A Bifet, B Pfahringer
Information Systems 83, 13-29, 2019
372019
Improving credit risk prediction in online peer-to-peer (p2p) lending using imbalanced learning techniques
LEB Ferreira, JP Barddal, HM Gomes, F Enembreck
2017 IEEE 29th International Conference on Tools with Artificial …, 2017
362017
SNCStream: A social network-based data stream clustering algorithm
JP Barddal, HM Gomes, F Enembreck
Proceedings of the 30th annual ACM symposium on applied computing, 935-940, 2015
362015
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
352020
Merit-guided dynamic feature selection filter for data streams
JP Barddal, F Enembreck, HM Gomes, A Bifet, B Pfahringer
Expert Systems with Applications 116, 227-242, 2019
352019
A survey on semi-supervised learning for delayed partially labelled data streams
HM Gomes, M Grzenda, R Mello, J Read, MH Le Nguyen, A Bifet
ACM Computing Surveys 55 (4), 1-42, 2022
332022
A survey on feature drift adaptation
JP Barddal, HM Gomes, F Enembreck
2015 IEEE 27th International Conference on Tools with Artificial …, 2015
322015
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