Heitor Murilo Gomes
I am a Machine Learning Researcher and Data Scientist. As of 2022, I became a Lecturer (Assistant Professor) in AI at the Victoria University of Wellington (New Zealand).
Selected Publications
A Survey on Semi-Supervised Learning for Delayed Partially Labelled Data Streams
H M Gomes, M Grzenda, R Mello, J Read, M H L Nguyen, A Bifet. ACM Computing Surveys, 2022. DOI: https://doi.org/10.1145/3523055
We organise methods that leverage unlabelled data in a semi-supervised setting for streaming data. We also discuss the delayed labelling issue, which impacts both fully supervised and semi-supervised methods.
Streaming Random Patches for Evolving Data Stream Classification
H M Gomes, J Read, A Bifet. IEEE International Conference on Data Mining (ICDM), 2019. DOI: https://doi.org/10.1109/ICDM.2019.00034
The Streaming Random Patches (SRP) algorithm outperforms the current state-of-the-art ensemble methods for evolving data stream classification. Access Paper
Machine learning for streaming data: state of the art, challenges, and opportunities
H M Gomes, J Read, A Bifet, J P Barddal, J Gama. SIGKDD Explorations Newsletter, ACM , 2019. DOI: https://doi.org/10.1145/3373464.3373470
In this work, we focus on elucidating the connections among the current stateof-the-art on related fields; and clarifying open challenges in both academia and industry. Access Paper
A Survey on Ensemble Learning for Data Stream Classification
H M Gomes, J P Barddal, F Enembreck, A Bifet. ACM Computing Surveys 50, 2, Article 23, 2017. DOI: https://doi.org/10.1145/3054925
This paper contains the most up to date and comprehensive survey about ensemble learning for data streams. Access Paper
Adaptive random forests for evolving data stream classification
H M Gomes, A Bifet, J Read, …, B Pfahringer, G Holmes, T Abdessalem. ACM Machine Learning, Springer, 2017. DOI: https://doi.org/10.1007/s10994-017-5642-8
This paper presents an efficent version of the classical Random Forests algorithm for evolving data streams, namely the Adaptive Random Forest (ARF) algorithm. Access Paper