Contact Details

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

• 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., Bifet, A., Maniu, S., De Mello, R. F., & Tziortziotis, N. (2020). Compressed k-nearest neighbors ensembles for evolving data streams. In G. De Giacomo, A. Catala, B. Dilkina, M. Milano, S. Barro, A. Bugarin, & J. Lang (Eds.), Proc 24th European Conference on Artificial Intelligence (ECAI 2020), Frontiers in Artificial Intelligence and Applications Vol. 325 (pp. 961-968). Santiago de Compostela, Spain: IOS Press. doi:10.3233/FAIA200189

• Bahri, M., Pfahringer, B., Bifet, A., & Maniu, S. (2020). Efficient batch-incremental classification using UMAP for evolving data streams. In M. R. Berthold, A. Feelders, & G. Krempl (Eds.), Proc Advances in Intelligent Data Analysis IVIII: 18th Symposium on Intelligent Data Analysis (IDA 2020) Vol. LNCS 12080 (pp. 40-53). Konstanz, Germany: Springer. doi:10.1007/978-3-030-44584-3_4

• Cortez, P., & Bifet, A. (2020). Fifth special issue on knowledge discovery and business intelligence. Expert Systems, Early View. doi:10.1111/exsy.12628

Find more research publications by Albert Bifet