Dr Heitor Murilo Gomes
Senior Research Fellow (Computer Science)
Qualifications: BSc UTP MSc PhD PUCPR
Contact Details
Email: hgomes@waikato.ac.nz
Room: FG.2.03
Phone: +64 7 838 4104
Website: https://www.heitorgomes.com
About Heitor Murilo
Since his undergraduate studies, Heitor focuses his research in machine learning and data mining. This has not changed since, but now he focuses mainly on machine learning for data streams.
Research Interests
Data stream mining, ensemble methods, semi-supervised learning, feature selection.
Recent Publications
Barddal, J. P., Enembreck, F., Gomes, H. M., Bifet, A., & Pfahringer, B. (2019). Merit-guided dynamic feature selection filter for data streams. Expert Systems with Applications, 116, 227-242. doi:10.1016/j.eswa.2018.09.031
Gomes, H. M., Mello, R. F. D., Pfahringer, B., & Bifet, A. (2019). Feature Scoring using Tree-Based Ensembles for Evolving Data Streams. In Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 761-769). doi:10.1109/BigData47090.2019.9006366
Grzenda, M., Gomes, H. M., & Bifet, A. (2019). Delayed labelling evaluation for data streams. Data Mining and Knowledge Discovery. doi:10.1007/s10618-019-00654-y
Gomes, H. M., Bifet, A., Fournier-Viger, P., Granatyr, J., & Read, J. (2019). Network of experts: Learning from evolving data streams through network-based ensembles. In Proc International Conference on Neural Information Processing (ICONIP 2019) LNCS 11953 (pp. 704-716). Sydney, Australia: Springer. doi:10.1007/978-3-030-36708-4_58