Dr Patricia Jean Riddle

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Senior Lecturer

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. Most of my applications focus is currently directed to Molecular Biology.

Find more information on my personal website.

Selected publications and creative works (Research Outputs)

  • 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, Diana Benavides Prado
  • Peng, A., Koh, Y., & 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 inComputer Science, vol. 10235), 10235 (Part 2), 196-207. Jeju, South Korea. 10.1007/978-3-319-57529-2_16
    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. Paper presented at Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR) and Statistical Techniques in Pattern Recognition (SPR), Merida, MEXICO. 29 November - 2 December 2016. STRUCTURAL, SYNTACTIC, AND STATISTICAL PATTERN RECOGNITION, S+SSPR 2016. (pp. 11). 10.1007/978-3-319-49055-7_34
    Other University of Auckland co-authors: Georgy Gimel'farb
  • Versteegen, R., Gimel'farb G, & Riddle, P. J. (2014). Learning High-order Generative Texture Models. IVCNZ '14 Proceedings of the 29th International Conference on Image and Vision Computing New Zealand, 90-95. Hamilton, New Zealand. 10.1145/2683405.2683420
    URL: http://hdl.handle.net/2292/24923
    Other University of Auckland co-authors: Georgy Gimel'farb
  • Alam, S., Dobbie, G., Koh, Y. S., Riddle, P., & Ur Rehman, S. (2014). Research on particle swarm optimization based clustering: A systematic review of literature and techniques. Swarm and Evolutionary Computation, 17, 1-13. 10.1016/j.swevo.2014.02.001
    Other University of Auckland co-authors: Gill Dobbie, Yun Sing Koh
  • Alam, S., Dobbie, G., Koh, Y. S., & Riddle, P. (2014). Web usage mining based recommender systems using implicit heterogeneous data: A Particle Swarm Optimization based clustering approach. Web Intelligence and Agent Systems, 12, 389-409. 10.3233/WIA-140302
    Other University of Auckland co-authors: Gill Dobbie, Yun Sing Koh
  • Alam, S., Dobbie, G., Koh, Y. S., & Riddle, P. (2014). Web Bots Detection Using Particle Swarm Optimization Based Clustering. Paper presented at IEEE Congress on Evolutionary Computation (CEC), Beijing, PEOPLES R CHINA. 6 July - 11 July 2014. 2014 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC). (pp. 8).
    Other University of Auckland co-authors: Yun Sing Koh, Gill Dobbie

Contact details

Primary location

SCIENCE CENTRE 303S - Bldg 303S
Level 4, Room 490
38 PRINCES ST
AUCKLAND 1010
New Zealand

Web links