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Dr Patricia Jean Riddle

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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)

As of 29 October 2020 there will be no automatic updating of 'selected publications and creative works' from Research Outputs. Please continue to keep your Research Outputs profile up to date.
  • Alcázar, V, Riddle, P., & Barley, M. (2020). A Unifying View on Individual Bounds and Heuristic Inaccuracies in Bidirectional Search. AAAI Press 2020, 2327-2334. New York, NY, USA. Related URL.
    Other University of Auckland co-authors: Michael Barley
  • Benavides-Prado, D., Koh, Y. S., & Riddle, P. (2020). Towards Knowledgeable Supervised Lifelong Learning Systems. JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 68, 159-224.
    Other University of Auckland co-authors: Yun Sing Koh
  • Peng, A. Y., koh, Y. S., Riddle, P. J., & Pfahringer, B. (2019). Investigating the effect of novel classes in semi-supervised learning. Proceedings of The Eleventh Asian Conference on Machine Learning, 101, 615-630. Nagoya, Japan. Related URL.
    Other University of Auckland co-authors: Yun Sing Koh
  • Alcázar V, Barley, M., & Riddle, P. (2019). A theoretical comparison of the bounds of MM, NBS, and GBFHS. Proceedings of the 12th International Symposium on Combinatorial Search, SoCS 2019.
  • Benavides-Prado, D., Koh, Y. S., & Riddle, P. (2019). Selective Hypothesis Transfer for Lifelong Learning. Paper presented at International Joint Conference on Neural Networks (IJCNN), Budapest, HUNGARY. 14 July - 19 July 2019. 2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN). (pp. 10).
    Other University of Auckland co-authors: Yun Sing Koh
  • Peng, A. Y., Sing Koh, Y., Riddle, P., & Pfahringer, B. (2019). Using supervised pretraining to improve generalization of neural networks on binary classification problems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-030-10925-7_25
    Other University of Auckland co-authors: Alex Peng, Yun Sing Koh
  • Hsu, W., Warren, J., & Riddle, P. (2019). Multivariate Sequential Analytics for Treatment Trajectory Forecasting. Paper presented at Australasian Computer Science Week Multiconference (ACSW), Sydney, AUSTRALIA. 29 January - 31 January 2019. PROCEEDINGS OF THE AUSTRALASIAN COMPUTER SCIENCE WEEK MULTICONFERENCE (ACSW 2019). (pp. 15). 10.1145/3290688.3290724
    Other University of Auckland co-authors: Jim Warren
  • Barley, M., Riddle, P., Linares López C, Dobson, S., & Pohl, I. (2018). GBFHS: A Generalized Breadth-First Heuristic Search Algorithm. Paper presented at The Eleventh Annual Symposium on Combinatorial Search, Stockholm, Sweden. 14 July - 15 July 2018. Proceedings of the Eleventh Annual Symposium on Combinatorial Search (SOCS 2018). (pp. 9). Related URL.
    Other University of Auckland co-authors: Michael Barley
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SCIENCE CENTRE 303S - Bldg 303S
Level 4, Room 490
38 PRINCES ST
AUCKLAND 1010
New Zealand

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