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Gavin C Cawley
Gavin C Cawley
Senior Lecturer in Computing Sciences, University of East Anglia
Verified email at uea.ac.uk - Homepage
Title
Cited by
Cited by
Year
On over-fitting in model selection and subsequent selection bias in performance evaluation
GC Cawley, NLC Talbot
The Journal of Machine Learning Research 11, 2079-2107, 2010
19212010
Efficient leave-one-out cross-validation of kernel fisher discriminant classifiers
GC Cawley, NLC Talbot
Pattern Recognition 36 (11), 2585-2592, 2003
4942003
Downscaling heavy precipitation over the United Kingdom: a comparison of dynamical and statistical methods and their future scenarios
MR Haylock, GC Cawley, C Harpham, RL Wilby, CM Goodess
International Journal of Climatology: A Journal of the Royal Meteorological …, 2006
4342006
Extensive evaluation of neural network models for the prediction of NO2 and PM10 concentrations, compared with a deterministic modelling system and measurements in central Helsinki
J Kukkonen, L Partanen, A Karppinen, J Ruuskanen, H Junninen, ...
Atmospheric Environment 37 (32), 4539-4550, 2003
3842003
Fast exact leave-one-out cross-validation of sparse least-squares support vector machines
GC Cawley, NLC Talbot
Neural networks 17 (10), 1467-1475, 2004
3792004
Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters.
GC Cawley, NLC Talbot
Journal of Machine Learning Research 8 (4), 2007
3312007
Establishing glucose-and ABA-regulated transcription networks in Arabidopsis by microarray analysis and promoter classification using a Relevance Vector Machine
Y Li, KK Lee, S Walsh, C Smith, S Hadingham, K Sorefan, G Cawley, ...
Genome research 16 (3), 414-427, 2006
3092006
Gene selection in cancer classification using sparse logistic regression with Bayesian regularization
GC Cawley, NLC Talbot
Bioinformatics 22 (19), 2348-2355, 2006
2842006
Sparse multinomial logistic regression via bayesian l1 regularisation
G Cawley, N Talbot, M Girolami
Advances in neural information processing systems 19, 2006
2692006
Leave-one-out cross-validation based model selection criteria for weighted LS-SVMs
GC Cawley
The 2006 IEEE international joint conference on neural network proceedings …, 2006
2622006
Model selection: Beyond the Bayesian/frequentist divide
I Guyon, A Saffari, G Dror, G Cawley
Journal of Machine Learning Research 11 (Jan), 61-87, 2010
1972010
A rigorous inter-comparison of ground-level ozone predictions
U Schlink, S Dorling, E Pelikan, G Nunnari, G Cawley, H Junninen, ...
Atmospheric Environment 37 (23), 3237-3253, 2003
1742003
Statistical models to assess the health effects and to forecast ground-level ozone
U Schlink, O Herbarth, M Richter, S Dorling, G Nunnari, G Cawley, ...
Environmental Modelling & Software 21 (4), 547-558, 2006
1462006
Modelling SO2 concentration at a point with statistical approaches
G Nunnari, S Dorling, U Schlink, G Cawley, R Foxall, T Chatterton
Environmental Modelling & Software 19 (10), 887-905, 2004
1322004
Non-retrieval: blocking pornographic images
A Bosson, GC Cawley, Y Chan, R Harvey
International Conference on Image and Video Retrieval, 50-60, 2002
1262002
Design of the 2015 chalearn automl challenge
I Guyon, K Bennett, G Cawley, HJ Escalante, S Escalera, TK Ho, N Macià, ...
2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015
1182015
Improved sparse least-squares support vector machines
GC Cawley, NLC Talbot
Neurocomputing 48 (1-4), 1025-1031, 2002
1082002
Results of the active learning challenge
I Guyon, GC Cawley, G Dror, V Lemaire
Active Learning and Experimental Design workshop In conjunction with AISTATS …, 2011
1002011
MATLAB support vector machine toolbox
GC Cawley
University of East Anglia, School of Information Systems, Norwich, Norfolk …, 2000
982000
Nested cross-validation when selecting classifiers is overzealous for most practical applications
J Wainer, G Cawley
Expert Systems with Applications 182, 115222, 2021
882021
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