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Professor Albert Bifet

Albert Bifet

Te Ipu o te Mahara AI Institute Director

Qualifications: PhD UPC

Personal Website: http://albertbifet.com/

About Albert

Albert is the Te Ipu o te Mahara AI Institute director. He 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 150 publications on machine learning methods and their applications.

Te Ipu o te Mahara AI Institute: https://ai.waikato.ac.nz/

Recent Publications

  • Cassales, G., Gomes, H., Bifet, A., Pfahringer, B., & Senger, H. (2021). Improving the performance of bagging ensembles for data streams through mini-batching. Information Sciences, 580, 260-282. doi:10.1016/j.ins.2021.08.085

  • del Campo-Ávila, J., Takilalte, A., Bifet, A., & Mora-López, L. (2021). Binding data mining and expert knowledge for one-day-ahead prediction of hourly global solar radiation. Expert Systems with Applications, 167(1). doi:10.1016/j.eswa.2020.114147

  • 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

  • Jia, Y., Frank, E., Pfahringer, B., Bifet, A., & Lim, N. (2021). Studying and exploiting the relationship between model accuracy and explanation quality. In N. Oliver, F. Pérez-Cruz, S. Kramer, J. Read, & J. A. Lozano (Eds.), Machine Learning and Knowledge Discovery in Databases. Research Track. ECML PKDD 2021. Lecture Notes in Computer Science Vol. 12976 (pp. 699-714). Cham: Springer. doi:10.1007/978-3-030-86520-7_43 Open Access version: https://hdl.handle.net/10289/14561

Find more research publications by Albert Bifet

Keywords

Data mining; Machine Learning

Artificial Intelligence