Biography

Website: http://theoval.cmp.uea.ac.uk/~gcc/

Follow this link for details of current PhD opportunities in Computing Sciences. But feel free to email me to discuss projects outside these areas and alternative sources of funding.

Academic Background

My principal research interests lie in machine learning, with a particular emphasis on Bayesian and kernel learning methods. I am most interested in theoretical issues and algorithms with a direct impact in the practical application of machine learning techniques, including topics such as feature selection, model selection, performance estimation, model comparison, covariate shift, dealing with imbalanced or "non-standard" data and semi-supervised learning. Most of my applied work centres on problems arising in computational biology, in collaboration with the School of Chemistry and Pharmacy (CAP) and with the nearby John Inness Centre (JIC) and Institute for Food Research (IFR). However I also have long-standing research links with the School of Environmental Sciences (ENV) and the Climatic Research Unit (CRU), working on applications of machine learning in the environmental sciences, particularly on modelling and exploiting predictive uncertainty.

All Publications

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Taylor, D., Cawley, G., Hayward, S.

(2014)

Quantitative method for the assignment of hinge and shear mechanism in protein domain movements

in Bioinformatics

Full Text UEA Repository

(Article)


Taylor, D., Cawley, G., Hayward, S.

(2013)

Classification of Protein Domain Movements using Dynamic Contact Graphs

in PLoS ONE

8.

Full Text UEA Repository

(Article)


Zhang, G., Ansari, H., Rahman, H., Cawley, G., Hertz, T., Hue, X., Jojic, N., Kim, Y., Kohlbacher, O., Lund, O., Lundegaardi, C., Magaret, C., Nielsen, M., Papadopoulos, H., Raghava, G., Tal, V., Xue, L., Yanover, C., Zhu, S., Rock, M., Crowe, J., Panayiotou, C., Polycarpou, M., Ducho, W., Brusic, V.

(2011)

Machine learning competition in immunology – Prediction of HLA class I binding peptides

in Journal of Immunological Methods

374.

pp. 1-4

Full Text UEA Repository

(Article)


Cawley, G., Talbot, N.

(2010)

On over-fitting in model selection and subsequent selection bias in performance evaluation

in Journal of Machine Learning Research

11.

pp. 2079-2107

UEA Repository

(Article)


Guyon, I., Saffari, A., Dror, G., Cawley, G.

(2010)

Model selection: Beyond the Bayesian/frequentist divide

in Journal of Machine Learning Research

11.

pp. 61-87

UEA Repository

(Article)


Cawley, G., Janacek, G.

(2010)

On allometric equations for predicting body mass of dinosaurs

in Journal of Zoology

280.

pp. 355-361

Full Text UEA Repository

(Article)


Cawley, G.

(2010)

Some Baseline Methods for the Active Learning Challenge

(Poster)


Guyon, I., Cawley, G., Dror, G., Lemaire, V.

(2010)

Design and Analysis of the WCCI 2010 Active Learning Challenge

Full Text UEA Repository

(Paper)


Cawley, G. C.

(2009)

Causal & non-causal feature selection for ridge regression

UEA Repository

(Paper)


Bagnall, A., Cawley, G., Whittley, I., Bull, L., Studley, M., Pettipher, M., Tekiner, F.

(2008)

Super Computer Heterogeneous Classifier Meta-Ensembles

In: Data Warehousing and Mining: Concepts, Methodologies, Tools and Applications.

IGI Global

pp. 1320-1333

ISBN 978-1599049519

UEA Repository

(Chapter)


Cawley, G., Talbot, N.

(2008)

Efficient approximate leave-one-out cross-validation for kernel logistic regression

in Machine Learning

71.

pp. 243-264

Full Text UEA Repository

(Article)


Guyon, I., Saffari, A., Dror, G., Cawley, G.

(2008)

Analysis of the IJCNN 2007 agnostic learning versus prior knowledge challenge

in Neural Networks

21.

pp. 544-550

Full Text UEA Repository

(Article)


Theobald, B., Cawley, G., Bangham, A., Matthews, I.

(2008)

Comparing text-driven and speech-driven visual speech synthesisers

UEA Repository

(Paper)


Saadi, K., Talbot, N., Cawley, G.

(2007)

Optimally regularised kernal Fisher discriminant classification

in Neural Networks

20.

pp. 832-841

Full Text UEA Repository

(Article)


Cawley, G., Janacek, G., Haylock, M., Dorling, S.

(2007)

Predictive uncertainty in environmental modelling

in Neural Networks

20.

pp. 537-549

Full Text UEA Repository

(Article)


Cawley, G., Talbot, N.

(2007)

Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters

in Journal of Machine Learning Research

8.

pp. 841-861

UEA Repository

(Article)


Bagnall, A., Cawley, G., Bull, L., Whittley, I., Studley, M., Pettipher, M., Tekiner, F.

(2007)

Super Computer Heterogeneous Classifier Meta-Ensembles

in International Journal of Data Warehousing and Mining (IJDWM)

3.

pp. 67-82

Full Text UEA Repository

(Article)


Cawley, G. C., Talbot, N. L. C.

(2007)

Agnostic learning versus prior knowledge in the design of kernel machines

Full Text UEA Repository

(Paper)


Cawley, G. C.

(2007)

Model selection for kernel probit regression

UEA Repository

(Paper)


Cawley, G. C., Janacek, G. J., Talbot, N. L. C.

(2007)

Generalised Kernel Machines

Full Text

(Other)


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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.

External Activities and Indicators of Esteem

  • 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 Responsibilities

Chair of Board of Examiners (Postgraduate Teaching)