Professor Albert Bifet

Professor (Computer Science)

Qualifications: PhD UPC

Contact Details

Room: FG.2.02
Phone: +64 7 838 4704
Extension: 4704

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:

Recent Publications

  • 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:

  • 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., 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

  • Bahri, M., Pfahringer, B., Bifet, A., & Maniu, S. (2020). Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12080 LNCS (pp. 40-53). doi:10.1007/978-3-030-44584-3_4

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