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Professor Albert Bifet

Albert Bifet

Professor (Computer Science)

Qualifications: PhD UPC

Personal Website: http://albertbifet.com/

About Albert

Albert is a computer scientist whose primary area of interest is Artificial Intelligence/Machine Learning for data streams and its applications. He is a core developer of the MOA machine learning software and has more than 120 publications on machine learning methods and their applications.

Waikato AI Initiative: https://ai.waikato.ac.nz/

Recent Publications

  • Haghir Chehreghani, M., Abdessalem, T., Bifet, A., & Bouzbila, M. (2020). Sampling informative patterns from large single networks. Future Generation Computer Systems, 106, 653-658. doi:10.1016/j.future.2020.01.042

  • Lobo, J. L., Del Ser, J., Bifet, A., & Kasabov, N. (2020). Spiking Neural Networks and online learning: An overview and perspectives. Neural Networks, 121, 88-100. doi:10.1016/j.neunet.2019.09.004 Open Access version: https://hdl.handle.net/10289/12963

  • Lobo, J. L., Oregi, I., Bifet, A., & Del Ser, J. (2020). Exploiting the stimuli encoding scheme of evolving Spiking Neural Networks for stream learning. Neural Networks, 123, 118-133. doi:10.1016/j.neunet.2019.11.021

  • Song, F., Diao, Y., Read, J., Stiegler, A., & Bifet, A. (2019). EXAD: A system for explainable anomaly detection on big data traces. In IEEE International Conference on Data Mining Workshops, ICDMW Vol. 2018-November (pp. 1435-1440). doi:10.1109/ICDMW.2018.00204

Find more research publications by Albert Bifet

Keywords

Data mining; Machine Learning


Contact Details

Email: abifet@waikato.ac.nz
Room: FG.2.02
Phone: +64 7 838 4704