Professor Eibe Frank
Professor (Computer Science)
Qualifications: Dipl-Inf Karlsruhe PhD Waikato
Personal Website: http://www.cs.waikato.ac.nz/~eibe/
Research Interests
Professor Frank is a computer scientist whose primary area of interest is machine learning and its applications. He is a core developer of the WEKA machine learning software and has more than 100 publications on machine learning methods and their application to data mining, text mining, and areas of research outside computer science.
Recent Publications
Falconer, J. R., Frank, E., Polaschek, D. L. L., & Joshi, C. (2022). Methods for eliciting informative prior distributions: A critical review. Decision Analysis. doi:10.1287/deca.2022.0451
Wang, H., Gouk, H., Fraser, H., Frank, E., Pfahringer, B., Mayo, M., & Holmes, G. (2022). Experiments in cross-domain few-shot learning for image classification. Journal of the Royal Society of New Zealand, 1-23. doi:10.1080/03036758.2022.2059767
Mitchell, R., Stokes, D., Frank, E., & Holmes, G. (2022). Bandwidth-optimal random shuffling for GPUs. ACM Transactions on Parallel Computing, 9(1). doi:10.1145/3505287
Mitchell, R., Frank, E., & Holmes, G. (2022). GPUTreeShap: massively parallel exact calculation of SHAP scores for tree ensembles. PeerJ Computer Science, 8, e880. doi:10.7717/peerj-cs.880 Open Access version: https://hdl.handle.net/10289/14815
Find more research publications by Eibe Frank
Keywords
Data mining; Machine Learning