Gavin C. Cawley

Publication Activity (10 Years)

Years Active: 1996-2021
Publications (10 Years): 11

Top Topics

Kernel Logistic Regression

Empirical Evaluation

Bayes Classifier

Hyperparameters

Top Venues

Publications

Matthew Middlehurst, James Large, Gavin C. Cawley, Anthony J. Bagnall
The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification. CoRR (2021)
Jacques Wainer, Gavin C. Cawley
Nested cross-validation when selecting classifiers is overzealous for most practical applications. Expert Syst. Appl. 182 (2021)
Ruth Veevers, Gavin C. Cawley, Steven Hayward
Investigation of sequence features of hinge-bending regions in proteins with domain movements using kernel logistic regression. BMC Bioinform. 21 (1) (2020)
Matthew Middlehurst, James Large, Gavin C. Cawley, Anthony J. Bagnall
The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification. ECML/PKDD (1) (2020)
Anthony J. Bagnall, Aaron Bostrom, Gavin C. Cawley, Michael Flynn, James Large, Jason Lines
Is rotation forest the best classifier for problems with continuous features? CoRR (2018)
Jacques Wainer, Gavin C. Cawley
Nested cross-validation when selecting classifiers is overzealous for most practical applications. CoRR (2018)
Rekar O. Mohammed, Gavin C. Cawley
Over-Fitting in Model Selection with Gaussian Process Regression. MLDM (2017)
Anthony J. Bagnall, Gavin C. Cawley
On the Use of Default Parameter Settings in the Empirical Evaluation of Classification Algorithms. CoRR (2017)
Jacques Wainer, Gavin C. Cawley
Empirical Evaluation of Resampling Procedures for Optimising SVM Hyperparameters. J. Mach. Learn. Res. 18 (2017)
Isabelle Guyon, Kristin P. Bennett, Gavin C. Cawley, Hugo Jair Escalante, Sergio Escalera, Tin Kam Ho, Núria Macià, Bisakha Ray, Mehreen Saeed, Alexander R. Statnikov, Evelyne Viegas
Design of the 2015 ChaLearn AutoML challenge. IJCNN (2015)
Awat A. Saeed, Gavin C. Cawley, Anthony J. Bagnall
Benchmarking the semi-supervised naïve Bayes classifier. IJCNN (2015)
Gavin C. Cawley, Nicola L. C. Talbot
Kernel learning at the first level of inference. Neural Networks 53 (2014)
Daniel Taylor, Gavin C. Cawley, Steven Hayward
Quantitative method for the assignment of hinge and shear mechanism in protein domain movements. Bioinform. 30 (22) (2014)
Gavin C. Cawley
Over-Fitting in Model Selection and Its Avoidance. IDA (2012)
Gavin C. Cawley, Steven Hayward, Gareth J. Janacek, Geoff R. Moore
Sparse Bayesian prediction of disordered residues and disordered regions based on amino-acid composition. IJCNN (2011)
Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire
Results of the Active Learning Challenge. Active Learning and Experimental Design @ AISTATS (2011)
Gavin C. Cawley
Baseline Methods for Active Learning. Active Learning and Experimental Design @ AISTATS (2011)
Gavin C. Cawley, Nicola L. C. Talbot
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation. J. Mach. Learn. Res. 11 (2010)
Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire
Design and analysis of the WCCI 2010 active learning challenge. IJCNN (2010)
Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C. Cawley
Model Selection: Beyond the Bayesian/Frequentist Divide. J. Mach. Learn. Res. 11 (2010)
Gavin C. Cawley
Causal and Non-Causal Feature Selection for Ridge Regression. WCCI Causation and Prediction Challenge (2008)
Barry-John Theobald, Gavin C. Cawley, J. Andrew Bangham, Iain A. Matthews, Nicholas Wilkinson
Comparing text-driven and speech-driven visual speech synthesisers. INTERSPEECH (2008)
Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C. Cawley
Analysis of the IJCNN 2007 agnostic learning vs. prior knowledge challenge. Neural Networks 21 (2-3) (2008)
Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C. Cawley
Agnostic Learning vs. Prior Knowledge Challenge. IJCNN (2007)
Gavin C. Cawley
Model Selection for Kernel Probit Regression. ESANN (2007)
Gavin C. Cawley, Gareth J. Janacek, Malcolm R. Haylock, Stephen R. Dorling
Predictive uncertainty in environmental modelling. Neural Networks 20 (4) (2007)
Gavin C. Cawley
An Empirical Evaluation of the Fuzzy Kernel Perceptron. IEEE Trans. Neural Networks 18 (3) (2007)
Gavin C. Cawley, Nicola L. C. Talbot
Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters. J. Mach. Learn. Res. 8 (2007)
Kamel Saadi, Nicola L. C. Talbot, Gavin C. Cawley
Optimally regularised kernel Fisher discriminant classification. Neural Networks 20 (7) (2007)
Anthony J. Bagnall, Gavin C. Cawley, Ian M. Whittley, Larry Bull, Matthew Studley, Mike Pettipher, Firat Tekiner
Super Computer Heterogeneous Classifier Meta-Ensembles. Int. J. Data Warehous. Min. 3 (2) (2007)
Gavin C. Cawley, Nicola L. C. Talbot
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines. IJCNN (2007)
Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. Talbot
Generalised Kernel Machines. IJCNN (2007)
Uwe Schlink, Olf Herbarth, Matthias Richter, Stephen R. Dorling, Giuseppe Nunnari, Gavin C. Cawley, Emil Pelikán
Statistical models to assess the health effects and to forecast ground-level ozone. Environ. Model. Softw. 21 (4) (2006)
Gavin C. Cawley, Nicola L. C. Talbot
Gene selection in cancer classification using sparse logistic regression with Bayesian regularization. Bioinform. 22 (19) (2006)
Jochen J. Steil, Gavin C. Cawley, Fabrice Rossi
New Issues in Neurocomputing. Neurocomputing 69 (7-9) (2006)
Gavin C. Cawley
Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs. IJCNN (2006)
Gavin C. Cawley, Nicola L. C. Talbot, Gareth J. Janacek, Mike W. Peck
Sparse bayesian kernel survival analysis for modeling the growth domain of microbial pathogens. IEEE Trans. Neural Networks 17 (2) (2006)
Gavin C. Cawley, Malcolm R. Haylock, Stephen R. Dorling
Predictive Uncertainty in Environmental Modelling. IJCNN (2006)
Gavin C. Cawley, Nicola L. C. Talbot, Mark A. Girolami
Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation. NIPS (2006)
Gavin C. Cawley, Nicola L. C. Talbot
The evidence framework applied to sparse kernel logistic regression. Neurocomputing 64 (2005)
Kee Khoon Lee, Gavin C. Cawley, Michael W. Bevan
sparse Bayesian promoter based gene classification. ESANN (2005)
Gavin C. Cawley, Nicola L. C. Talbot
Constructing Bayesian formulations of sparse kernel learning methods. Neural Networks 18 (5-6) (2005)
Gavin C. Cawley, Nicola L. C. Talbot, Olivier Chapelle
Estimating Predictive Variances with Kernel Ridge Regression. MLCW (2005)
Jochen J. Steil, Gavin C. Cawley, Thomas Villmann
Trends in Neurocomputing at ESANN 2004. Neurocomputing 64 (2005)
Gavin C. Cawley, Nicola L. C. Talbot
Sparse Bayesian kernel logistic regression. ESANN (2004)
Barry-John Theobald, J. Andrew Bangham, Iain A. Matthews, Gavin C. Cawley
Near-videorealistic synthetic talking faces: implementation and evaluation. Speech Commun. 44 (1-4) (2004)
Gavin C. Cawley, Nicola L. C. Talbot
Efficient Model Selection for Kernel Logistic Regression. ICPR (2) (2004)
Kamel Saadi, Nicola L. C. Talbot, Gavin C. Cawley
Optimally Regularised Kernel Fisher Discriminant Analysis. ICPR (2) (2004)
Gavin C. Cawley, Nicola L. C. Talbot
Fast exact leave-one-out cross-validation of sparse least-squares support vector machines. Neural Networks 17 (10) (2004)
Giuseppe Nunnari, Stephen R. Dorling, Uwe Schlink, Gavin C. Cawley, Robert J. Foxall, Tim J. Chatterton
concentration at a point with statistical approaches. Environ. Model. Softw. 19 (10) (2004)
Gavin C. Cawley, Nicola L. C. Talbot, Gareth J. Janacek, Michael W. Peck
Bayesian Kernel Learning Methods for Parametric Accelerated Life Survival Analysis. Deterministic and Statistical Methods in Machine Learning (2004)
Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Foxall, Stephen R. Dorling, Danilo P. Mandic
Heteroscedastic kernel ridge regression. Neurocomputing 57 (2004)
Barry-John Theobald, J. Andrew Bangham, Iain A. Matthews, John R. W. Glauert, Gavin C. Cawley
2.5D Visual Speech Synthesis Using Appearance Models. BMVC (2003)
Barry-John Theobald, Gavin C. Cawley, Iain A. Matthews, J. Andrew Bangham
Near-videorealistic synthetic visual speech using non-rigid appearance models. ICASSP (5) (2003)
Barry-John Theobald, Silko Kruse, J. Andrew Bangham, Gavin C. Cawley
Towards a low bandwidth talking face using appearance models. Image Vis. Comput. 21 (13-14) (2003)
Stephen J. Cox, Gavin C. Cawley
The use of confidence measures in vector based call-routing. INTERSPEECH (2003)
Gavin C. Cawley, Nicola L. C. Talbot
Efficient leave-one-out cross-validation of kernel fisher discriminant classifiers. Pattern Recognit. 36 (11) (2003)
Gavin C. Cawley, Nicola L. C. Talbot
Efficient cross-validation of kernel fisher discriminant classifiers. ESANN (2003)
Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Foxall, Stephen R. Dorling, Danilo P. Mandic
Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression. ESANN (2003)
Barry-John Theobald, J. Andrew Bangham, Iain A. Matthews, Gavin C. Cawley
Evaluation of a talking head based on appearance models. AVSP (2003)
Gavin C. Cawley, Malcolm R. Haylock, Stephen R. Dorling, Clare Goodess, Phil D. Jones
Statistical downscaling with artificial neural networks. ESANN (2003)
Gavin C. Cawley, Nicola L. C. Talbot
A Greedy Training Algorithm for Sparse Least-Squares Support Vector Machines. ICANN (2002)
Alison Bosson, Gavin C. Cawley, Yi Chan, Richard W. Harvey
Non-retrieval: Blocking Pornographic Images. CIVR (2002)
Barry-John Theobald, J. Andrew Bangham, Iain A. Matthews, Gavin C. Cawley
Towards video realistic synthetic visual speech. ICASSP (2002)
Robert J. Foxall, Gavin C. Cawley, Stephen R. Dorling, Danilo P. Mandic
Error Functions for Prediction of Episodes of Poor Air Quality. ICANN (2002)
Gavin C. Cawley, Nicola L. C. Talbot
Efficient formation of a basis in a kernel induced feature space. ESANN (2002)
Gavin C. Cawley, Nicola L. C. Talbot
Improved sparse least-squares support vector machines. Neurocomputing 48 (1-4) (2002)
Kamel Saadi, Gavin C. Cawley, Nicola L. C. Talbot
Fast exact leave-one-out cross-validation of least-squares Support Vector Machines. ESANN (2002)
Gavin C. Cawley, Nicola L. C. Talbot
Reduced Rank Kernel Ridge Regression. Neural Process. Lett. 16 (3) (2002)
Robert J. Foxall, Gavin C. Cawley, Nicola L. C. Talbot, Stephen R. Dorling, Danilo P. Mandic
Heteroscedastic regularised kernel regression for prediction of episodes of poor air quality. ESANN (2002)
Olli Yli-Harja, Pertti Koivisto, J. Andrew Bangham, Gavin C. Cawley, Richard W. Harvey, Ilya Shmulevich
Simplified implementation of the recursive median sieve. Signal Process. 81 (7) (2001)
Robert J. Foxall, Igor R. Krcmar, Gavin C. Cawley, Stephen R. Dorling, Danilo P. Mandic
Nonlinear modelling of air pollution time series. ICASSP (2001)
Barry-John Theobald, Gavin C. Cawley, Silko Kruse, J. Andrew Bangham
Towards a low bandwidth talking face using appearance models. BMVC (2001)
Barry-John Theobald, J. Andrew Bangham, Iain A. Matthews, Gavin C. Cawley
Visual speech synthesis using statistical models of shape and appearance. AVSP (2001)
Gavin C. Cawley
On a Fast, Compact Approximation of the Exponential Function. Neural Comput. 12 (9) (2000)
J. Andrew Bangham, Javier Ruiz Hidalgo, Richard W. Harvey, Gavin C. Cawley
The Segmentation of Images via Scale-Space Trees. BMVC (1998)
Nicola L. C. Talbot, Gavin C. Cawley
A Fast Index Assignment Method for Robust Vector Quantization of Image Data. ICIP (3) (1997)
Luis Miguel Teixeira de Jesus, Gavin C. Cawley
Speech coding and synthesis using parametric curves. EUROSPEECH (1997)
Gavin C. Cawley
An improved vector quantization algorithm for speech transmission over noisy channels. ICSLP (1996)
Gavin C. Cawley, Stephen R. Dorling
Reproducing a Subjective Classification Scheme for Atmospheric Circulation Patterns over the United Kingdom Using a Neural Network. ICANN (1996)