| 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 | 1163 | 2010 |
| Efficient leave-one-out cross-validation of kernel fisher discriminant classifiers GC Cawley, NLC Talbot Pattern Recognition 36 (11), 2585-2592, 2003 | 435 | 2003 |
| 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 | 402 | 2006 |
| 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 | 336 | 2004 |
| 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 | 332 | 2003 |
| Preventing over-fitting during model selection via Bayesian regularisation of the hyper-parameters GC Cawley, NLC Talbot Journal of Machine Learning Research 8 (Apr), 841-861, 2007 | 280 | 2007 |
| 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 | 280 | 2006 |
| Gene selection in cancer classification using sparse logistic regression with Bayesian regularization GC Cawley, NLC Talbot Bioinformatics 22 (19), 2348-2355, 2006 | 250 | 2006 |
| 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 | 234 | 2006 |
| Sparse multinomial logistic regression via bayesian l1 regularisation GC Cawley, NL Talbot, M Girolami Advances in neural information processing systems, 209-216, 2007 | 232 | 2007 |
| 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 | 167 | 2010 |
| 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 | 152 | 2003 |
| 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 | 135 | 2006 |
| 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 | 125 | 2004 |
| Non-retrieval: blocking pornographic images A Bosson, GC Cawley, Y Chan, R Harvey International Conference on Image and Video Retrieval, 50-60, 2002 | 123 | 2002 |
| Improved sparse least-squares support vector machines GC Cawley, NLC Talbot Neurocomputing 48 (1-4), 1025-1031, 2002 | 103 | 2002 |
| MATLAB support vector machine toolbox GC Cawley University of East Anglia, School of Information Systems, Norwich, Norfolk …, 2000 | 92 | 2000 |
| 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 | 81 | 2011 |
| 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 | 71 | 2015 |
| Efficient approximate leave-one-out cross-validation for kernel logistic regression GC Cawley, NLC Talbot Machine Learning 71 (2-3), 243-264, 2008 | 66 | 2008 |
Nicola TalbotUniversity of East AngliaVerified email at cmp.uea.ac.uk
