Research Publications for Heitor M Gomes
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Manapragada, C., Gomes, H. M., Salehi, M., Bifet, A., & Webb, G. I. (2022). An eager splitting strategy for online decision trees in ensembles. Data Mining and Knowledge Discovery. doi:10.1007/s10618-021-00816-x
Petri, I., Chirila, I., Gomes, H., Bifet, A., & Rana, O. (2022). Resource-Aware Edge-Based Stream Analytics. IEEE Internet Computing. doi:10.1109/MIC.2022.3152478
Cassales, G., Gomes, H., Bifet, A., Pfahringer, B., & Senger, H. (2021). Improving the performance of bagging ensembles for data streams through mini-batching. Information Sciences, 580, 260-282. doi:10.1016/j.ins.2021.08.085
Schmidt, L., Casanova, D., Ribeiro, R., Teixeira, M., & Gomes, H. M. (2021). A combined solution for flexible control of poultry houses. International Journal of Computer Applications in Technology, 67(2-3), 232-243. doi:10.1504/IJCAT.2021.121539
Other publications by:
GOMES, Heitor MChanajitt, R., Pfahringer, B., & Gomes, H. M. (2021). Combining static and dynamic analysis to improve machine learning-based malware classification. In 2021 IEEE 8th International Conference on Data Science and Advanced Analytics. doi:10.1109/DSAA53316.2021.9564144
Gomes, H., Read, J., Bifet, A., & Durrant, R. J. (2021). Learning from evolving data streams through ensembles of random patches. Knowledge and Information Systems, 63(7), 1597-1625. doi:10.1007/s10115-021-01579-z
Gomes, H. M., Grzenda, M., Mello, R., Read, J., Nguyen, M. H. L., & Bifet, A. (2021). A survey on semi-supervised learning for delayed partially labelled data streams. arXiv. Retrieved from http://arxiv.org/abs/2106.09170v1
Mastelini, S. M., Montiel, J., Gomes, H. M., Bifet, A., Pfahringer, B., & De Carvalho, A. C. P. L. F. (2021). Fast and lightweight binary and multi-branch Hoeffding Tree Regressors. In IEEE International Conference on Data Mining Workshops, ICDMW Vol. 2021-December (pp. 380-388). doi:10.1109/ICDMW53433.2021.00053
Bahri, M., Bifet, A., Gama, J., Gomes, H. M., & Maniu, S. (2021). Data stream analysis: foundations, major tasks and tools. WIREs: Data Mining and Knowledge Discovery, 11(3). doi:10.1002/widm.1405
Montiel, J., Halford, M., Mastelini, S. M., Bolmier, G., Sourty, R., Vaysse, R., . . . Bifet, A. (2021). River: Machine learning for streaming data in Python. Journal of Machine Learning Research, 22(10), 1-8. Retrieved from http://jmlr.org/papers/v22/20-1380.html
Open Access version at:
https://hdl.handle.net/10289/14402
Other publications by:
BIFET FIGUEROL, Albert C :: MONTIEL LOPEZ, Jacob :: GOMES, Heitor M
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