Projects per year
Personal profile
Academic Background
Biography
Website: http://theoval.cmp.uea.ac.uk/~gcc/
Follow this link for details of current PhD opportunities in Computing Sciences. I am not currently available to supervise PhD projects.
External Activities
- MRC Discipline-hopping Fellowship, 2004
- Joint Editor, Special Issue of Neurocomputing, 2003 and 2004
- Co-chair Multi-level Optimisation Workshop at NIPS-2006
- Co-chaired the workshop on Agnostic Learning versus Prior Knowledge at IJCNN-2007
Key Research Interests
Gavin Cawley is part of the Computational Biology Group and the Knowledge Discovery and Data Mining Group
Gavin's current research interests include a continuation of his post-graduate research on neural networks in speech synthesis, and classification of atmospheric circulation patterns (also using neural networks), in collaboration with Dr Steve Dorling.
Selected Publications:
Saadi, K., Talbot, N.L.C., and Cawley, G.C. Optimally regularised kernel Fisher discriminant classification. Neural Networks, Volume 20, Issue 7, Page(s) 832-841, 2007.
Cawley, G. C. and Talbot, N. L. C. Preventing over-fitting during model selection using Bayesian regularisation. Journal of Machine Learning Research, Volume 8, Page(s) 841-861, 2007.
Cawley, G. C. and Talbot, N. L. C. Gene selection in cancer classification using sparse logistic regression with Bayesian regularisation. Bioinformatics, Volume 22, Number 19, Page(s) 2348-2355, 2006.
Cawley, G. C. and Talbot, N. L. C. Efficient leave-one-out cross-validation of kernel Fisher discriminant classifiers. Pattern Recognition, Volume 36, Issue 11, Page(s) 2585-2592, 2003.
Key Responsibilities
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Network
Projects
- 2 Finished
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Smart Environments Research Facility
Lettice, F., Aung, M. H., Bagnall, T., Buckley, O., Cawley, G., Day, A., De La Iglesia, B., Finlayson, G., Harvey, R., Huber, K., Kulinskaya, E., Laycock, S., Lines, J., Mackiewicz, M., Milner, B., Moulton, V., Parr, G., Ren, E. & Wang, W.
Engineering and Physical Sciences Research Council
10/01/20 → 8/07/22
Project: Research
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Advancing Machine Learning Methodology for New Classes of Prediction Problems
Cawley, G., Hayward, S. & Moore, G.
Engineering and Physical Sciences Research Council
25/02/08 → 24/08/11
Project: Research
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Nested cross-validation when selecting classifiers is overzealous for most practical applications
Wainer, J. & Cawley, G., 15 Nov 2021, In: Expert Systems with Applications. 182, 115222.Research output: Contribution to journal › Article › peer-review
Open AccessFile35 Citations (Scopus)8 Downloads (Pure) -
The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification
Middlehurst, M., Large, J., Cawley, G. & Bagnall, A., 25 Feb 2021, p. 660-676. 17 p.Research output: Contribution to conference › Paper › peer-review
Open AccessFile11 Citations (Scopus)2 Downloads (Pure) -
Investigation of sequence features of hinge-bending regions in proteins with domain movements using kernel logistic regression
Veevers, R., Cawley, G. & Hayward, S., 9 Apr 2020, In: BMC Bioinformatics. 21, 137.Research output: Contribution to journal › Article › peer-review
Open AccessFile11 Downloads (Pure) -
Empirical evaluation of resampling procedures for optimising SVM hyperparameters
Wainer, J. & Cawley, G., 1 Feb 2017, In: Journal of Machine Learning Research. 18, 15, p. 1-35 35 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile32 Citations (Scopus)8 Downloads (Pure) -
Over-Fitting in Model Selection with Gaussian Process Regression
Mohammed, R. O. & Cawley, G. C., 15 Jul 2017, Machine Learning and Data Mining in Pattern Recognition: 13th International Conference, MLDM 2017, New York, NY, USA, July 15-20, 2017, Proceedings. Perner, P. (ed.). 1 ed. Springer, Vol. 10358. p. 192-205 14 p. (Lecture Notes in Computer Science)(Lecture Notes in Artificial Intelligence).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile16 Citations (Scopus)58 Downloads (Pure)