Research Publications for Geoffrey Holmes

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Author's Publications

Publications ByHOLMES, Geoffrey

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  • Leathart, T., Frank, E., Pfahringer, B., & Holmes, G. (2019). Ensembles of nested dichotomies with multiple subset evaluation. In Q. Yang, Z. -H. Zhou, Z. Gong, M. -L. Zhang, & S. -J. Huang (Eds.), Advances in Knowledge Discovery and Data Mining: Proc 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2019), LNCS 11439 Vol. Part I (pp. 81-93). Cham: Springer. doi:10.1007/978-3-030-16148-4_7

  • Leathart, T., Frank, E., Pfahringer, B., & Holmes, G. (2019). On calibration of nested dichotomies. In Q. Yang, Z. -H. Zhou, Z. Gong, M. -L. Zhang, & S. -J. Huang (Eds.), Advances in Knowledge Discovery and Data Mining: Proc 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2019), LNCS 11439 Vol. Part I (pp. 69-80). Cham: Springer. doi:10.1007/978-3-030-16148-4_6

  • Sharifi, N., Chen, Y., Holmes, G., Cheang, U. K., & Gong, Z. (2019). Model predictive control strategy for navigating nanoswimmers in blood vessels using taxicab geometry. In IEEE International Conference on Nano/Molecular Medicine and Engineering Vol. 2020-November (pp. 163-166). doi:10.1109/NANOMED49242.2019.9130625

  • Bifet, A., Read, J., Holmes, G., & Pfahringer, B. (2018). Streaming data mining with Massive Online Analytics (MOA). In M. Last, H. Bunke, & A. Kandel (Eds.), Data Mining in Time Series and Streaming Databases (pp. 1-25). doi:10.1142/9789813228047_0001

  • Bifet, A., Gavaldà, R., Pfahringer, B., & Holmes, G. (2018). Machine learning for data streams with practical examples in MOA. MIT Press. Retrieved from https://mitpress.mit.edu/books/machine-learning-data-streams

  • Chen, Y., Zhou, Y., Sharifi, N., Murch, R., & Holmes, G. (2018). Drug delivery via nanomachines. In X. Shen, X. Lin, & K. Zhang (Eds.), Encyclopedia of Wireless Networks (pp. 1-7). Cham: Springer. doi:10.1007/978-3-319-32903-1_224-1

  • Gibert, K., Horsburgh, J. S., Athanasiadis, I. N., & Holmes, G. (2018). Environmental data science. Environmental Modelling & Software, 106, 4-12. doi:10.1016/j.envsoft.2018.04.005

  • van Rijn, J. N., Holmes, G., Pfahringer, B., & Vanschoren, J. (2018). The online performance estimation framework: heterogeneous ensemble learning for data streams. Machine Learning, 107(1), 149-176. doi:10.1007/s10994-017-5686-9

  • Gibert, K., Izquierdo, J., Sànchez-Marrè, M., Hamilton, S. H., Rodríguez-Roda, I., & Holmes, G. (2018). Which method to use? An assessment of data mining methods in Environmental Data Science. Environmental Modelling and Software, 110, 3-27. doi:10.1016/j.envsoft.2018.09.021

  • Chen, Y., Sharifi, N., & Holmes, G. (2018). Biosensing by learning: cancer detection as iterative optimization. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1837-1840). Conference held at Honolulu, Hawaii: IEEE. doi:10.1109/EMBC.2018.8512705


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