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Professor Albert Bifet

Professor (Computer Science)

Qualifications: PhD UPC

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

  • Mordvanyuk, N., López, B., & Bifet, A. (2021). vertTIRP: Robust and efficient vertical frequent time interval-related pattern mining. Expert Systems with Applications, 168. doi:10.1016/j.eswa.2020.114276

  • Zhang, W., & Bifet, A. (2020). FEAT: A fairness-enhancing and concept-adapting decision tree classifier. In A. Appice, G. Tsoumakas, Y. Manolopoulos, & S. Matwin (Eds.), Proc 23rd International Conference on Discovery Science (DS 2020) Vol. LNAI 12323 (pp. 175-189). Thessaloniki, Greece: Springer. doi:10.1007/978-3-030-61527-7_12

  • Cerqueira, V., Gomes, H. M., & Bifet, A. (2020). Unsupervised concept drift detection using a student–teacher approach. In A. Appice, G. Tsoumakas, Y. Manolopoulos, & S. Matwin (Eds.), Proc 23rd International Conference on Discovery Science (DS 2020) Vol. LNAI 12323 (pp. 190-204). Thessaloniki, Greece: Springer. doi:10.1007/978-3-030-61527-7_13

  • Losing, V., Hammer, B., Wersing, H., & Bifet, A. (2020). Randomizing the self-adjusting memory for enhanced handling of concept drift. In Proc 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). Glasgow, UK: IEEE. doi:10.1109/IJCNN48605.2020.9207583

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