Research Publications for Eibe T Frank

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Author's Publications

Publications ByFRANK, Eibe T

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  • Mitchell, R., & Frank, E. (2017). Accelerating the XGBoost algorithm using GPU computing. PeerJ Computer Science, 3. doi:10.7717/peerj-cs.127

  • Gurulian, I., Shepherd, C., Frank, E., Markantonakis, K., Akram, R. N., & Mayes, K. (2017). On the effectiveness of ambient sensing for detecting NFC relay attacks. In Proc 16th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (pp. 41-49). Sydney, Australia: IEEE. doi:10.1109/Trustcom/BigDataSE/ICESS.2017.218

  • Geilke, M., Karwath, A., Frank, E. T., & Kramer, S. (2017). Online estimation of discrete, continuous, and conditional joint densities using classifier chains. Data Mining and Knowledge Discovery, Online first, 1-43. doi:10.1007/s10618-017-0546-6

  • Leathart, T., Frank, E., Holmes, G., & Pfahringer, B. (2017). Probability calibration trees. In M. -L. Zhang, & Y. -K. Noh (Eds.), Proc 9th Asian Conference on Machine Learning Vol. PMLR 77 (pp. 145-160). Seoul, Korea. Retrieved from http://proceedings.mlr.press/v77/leathart17a.html

  • Shepherd, C., Gurulian, I., Frank, E., Markantonakis, K., Akram, R. N., Panaousis, E., & Mayes, K. (2017). The applicability of ambient sensors as proximity evidence for NFC transactions. In Proc Mobile Security Technologies (MOST) 2017 (pp. 10 pages). San Jose, CA: IEEE Computer Society.

  • Mo, J., Frank, E., & Vetrova, V. (2017). Large-scale automatic species identification. In W. Peng, D. Alahakoon, & X. Li (Eds.), Proc 30th Australasian Joint Conference on Advances in Artificial Intelligence Vol. LNAI 10400 (pp. 301-312). Melbourne, Australia: Springer. doi:10.1007/978-3-319-63004-5_24

  • Gurulian, I., Markantonakis, K., Shepherd, C., Frank, E., & Akram, R. J. (2017). Proximity assurances based on natural and artificial ambient environments. In P. Farshim, & E. Simion (Eds.), Innovative Security Solutions for Information Technology and Communications. SecITC 2017 (pp. 83-103). Cham: Spinger. doi:10.1007/978-3-319-69284-5_7

  • Bravo Marquez, F., Frank, E., & Pfahringer, B. (2016). From opinion lexicons to sentiment classification of tweets and vice versa: a transfer learning approach. In Proc 2016 IEEE/WIC/ACM International Conference on Web Intelligence (pp. 145-152). Omaha, Nebraska, USA: IEEE Computer Society. doi:10.1109/WI.2016.29

  • Leathart, T., Pfahringer, B., & Frank, E. (2016). Building ensembles of adaptive nested dichotomies with random-pair selection. In P. Frasconi, N. Landwehr, G. Manco, & J. Vreeken (Eds.), Proc Joint European Conference on Machine Learning and Knowledge Discovery in Databases Vol. Part II, LNAI 9852 (pp. 179-194). Riva del Garda, Italy: Springer. doi:10.1007/978-3-319-46227-1_12

  • Smith, T. C., & Frank, E. (2016). Introducing machine learning concepts with WEKA. In E. Mathé, & S. Davis (Eds.), Statistical Genomics: Methods and Protocols (Vol. 1418, pp. 353-378). Springer. doi:10.1007/978-1-4939-3578-9_17

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