I am a machine learning researcher and developer working at the University of Waikato (New Zealand).
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
- (December 2020) Students, New MOA version
- New PhD student starting on February
- Organized a joint ML seminar with the University of Auckland
- A new MOA version was released (2020.12). Highlights: new feature analysis tab, new feature importance algorithms, new meta-classifiers for imbalanced classification, kNN for regression. A tutorial about using the novel feature analysis and feature importance tab is available here.
- (November 2020) Papers
- Paper accepted at HPCC 2020
- I am responsible for the international collaborations between UoW and Cardiff University w.r.t AI research
- (October 2020) Papers, Students and IEEE ICDM 2021
- Papers accepted at IEEE Big Data 2020 and ROOTS 2020
- I am the Online Experience/Virtual Chair of ICDM 2021
- Two master students and one honour student finished this month
- (September 2020) New website
- Going through the process of migrating stuff from the old website to the new one.
- I am co-chair of the DS track at ACM SAC 2021. Read more
- Attending ECML 2020.
- (August 2020) The MOA Lab
- The MOA Lab is open (University of Waikato, FG Link building).
- One week vacations in the South Island :)
- (July 2020) scikit-multiflow and papers
- (June 2020) COMPX523 wrap-up and papers!
- Paper accepted at DAWAK 2020.
- COMPX523 (Data stream mining) 2020 has ended. It was interesting to teach over Zoom, but I prefer to teach in a classroom.
- (May 2020) Chaired a Session for PAKDD 2020
- Sequential/Dynamic Data + Recommendation System (2) + Novel Algorithm PAKDD Session. This was nice and a bit exhausting (3 hours+).
- (April 2020) Honour Roll of Outstanding Reviewers for PAKDD 2020
- Twenty-two reviewers (out of more than four hundred) were selected to the Honour Roll of Outstanding Reviewers for PAKDD 2020. I am one of the twenty-two :)
- (March 2020) COMPX523 and paper
- Paper accepted at IJCAI 2020
- COMPX523 Data stream mining paper started at UoW. It was quickly moved to online teaching due to the lockdown.
- Tutorial 6: Building MOA from the source. Read more.
(February 2020) Three papers accepted at IJCNN 2020
- (January 2020) Distributed ML DS Project kick-off