Dr Patricia Jean Riddle

Senior Lecturer

In: School of Computer Science » Faculty of Science

Research | Current

My main research interests are in the AI areas of machine learning and datamining.

In particular, I am interested in various techniques for machine learning (such as ensemble approaches, techniques which overcome overfitting problems, and data-engineering as incorporating background knowledge) and their applications to real world problems. In additon I have been working in the area of search, planning, and representation increasingly in the last few years.

Find more information on my personal website.

Selected publications and creative works (Research Outputs)

Fuentetaja, R., Barley, M. W., Borrajo, D., Douglas, J., Franco, S., & Riddle, P. (17/6/2017). Meta-search through the space of representations and heuristics on a problem by problem basis. Poster presented at SoCS 2017: The 10th Annual Symposium on Combinatorial Search, Pittsburgh, Pennsylvania, USA.
Other University of Auckland co-authors: Michael Barley
Benavides-Prado, D., Koh, Y., & Riddle, P. (2017). AccGenSVM: Selectively transferring from previous hypotheses. In C. Sierra (Ed.) Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 1440-1446. Melbourne, Australia.
Other University of Auckland co-authors: Yun Sing Koh
Peng, A. Y., Koh, Y. S., & Riddle, P. (2017). mHUIMiner: A fast high utility itemset mining algorithm for sparse datasets. In J. Kim, K. Shim, L. Cao, J. G. Lee, X. Lin, Y. S. Moon (Eds.) Advances in Knowledge Discovery and Data Mining: 21st Pacific-Asia Conference, PAKDD 2017 (Lecture Notes in Computer Science), 10235 (Part 2), 196-207. Jeju, South Korea. 10.1007/978-3-319-57529-2_16
URL: http://hdl.handle.net/2292/38686
Other University of Auckland co-authors: Yun Sing Koh, Alex Peng
Versteegen, R., Gimel'farb G, & Riddle, P. (2016). Texture modelling with nested high-order Markov–Gibbs random fields. Computer Vision and Image Understanding, 143, 120-134. 10.1016/j.cviu.2015.11.003
URL: http://hdl.handle.net/2292/30306
Other University of Auckland co-authors: Georgy Gimel'farb
Versteegen, R., Gimel'farb G, & Riddle, P. (2016). Markov-gibbs texture modelling with learnt freeform filters. In A. Robles-Kelly, M. Loog, B. Biggio, F. Escolano, R. Wilson (Eds.) Structural, Syntactic, and Statistical Pattern Recognition Joint IAPR International Workshop, S+SSPR 2016, Proceedings, LNCS, volume 10029, 379-389. Mérida, Mexico: SPRINGER INT PUBLISHING AG. 10.1007/978-3-319-49055-7_34
Other University of Auckland co-authors: Georgy Gimel'farb
Chen, K., Koh, Y. S., & Riddle, P. (2016). Proactive drift detection: Predicting concept drifts in data streams using probabilistic networks. Proceedings of the International Joint Conference on Neural Networks, 780-787. Vancouver, Canada: IEEE. 10.1109/IJCNN.2016.7727279
URL: http://hdl.handle.net/2292/41721
Other University of Auckland co-authors: Kylie Chen, Yun Sing Koh
Versteegen, R., Gimel'farb G, & Riddle, P. (2015). Texture Modelling with Non-contiguous Filters. Paper presented at International Conference on Image and Vision Computing New Zealand (IVCNZ), Auckland, NEW ZEALAND. 23 November - 24 November 2015. 2015 INTERNATIONAL CONFERENCE ON IMAGE AND VISION COMPUTING NEW ZEALAND (IVCNZ). (pp. 6).
Other University of Auckland co-authors: Georgy Gimel'farb
Riddle, P. J., Barley, M., Franco, S., & Douglas, J. (2015). Automated transformation of PDDL representations. In L. Lelis, R. Stern (Eds.) Proceedings of the Eighth Annual Symposium on Combinatorial Search, SOCS 2015, 11-13 June 2015, Ein Gedi, the Dead Sea, Israel, 214-215. Ein Gedi, the Dead Sea, Israel: AAAI PRESS.
Other University of Auckland co-authors: Michael Barley, Jordan Douglas