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Professor Eibe Frank

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

  • Holmes, G., Frank, E., Fletcher, D., & Sterling, C. (2022). Efficiently correcting machine learning: considering the role of example ordering in human-in-the-loop training of image classification models. In Proc 27th International Conference on Intelligent User Interfaces (IUI '22) (pp. 584-593). New York, NY, USA: ACM. doi:10.1145/3490099.3511110

  • 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

  • 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

  • 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