Gavin C. Cawley

According to our database, Gavin C. Cawley authored at least 77 papers between 1996 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Nested cross-validation when selecting classifiers is overzealous for most practical applications.

Jacques Wainer, Gavin C. Cawley

Expert Syst. Appl., 2021

2020

Investigation of sequence features of hinge-bending regions in proteins with domain movements using kernel logistic regression.

Ruth Veevers, Gavin C. Cawley, Steven Hayward

BMC Bioinform., 2020

The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification.

Matthew Middlehurst, James Large, Gavin C. Cawley, Anthony J. Bagnall

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

2018

Is rotation forest the best classifier for problems with continuous features?

Anthony J. Bagnall, Aaron Bostrom, Gavin C. Cawley, Michael Flynn, James Large, Jason Lines

CoRR, 2018

2017

Empirical Evaluation of Resampling Procedures for Optimising SVM Hyperparameters.

Jacques Wainer, Gavin C. Cawley

J. Mach. Learn. Res., 2017

On the Use of Default Parameter Settings in the Empirical Evaluation of Classification Algorithms.

Anthony J. Bagnall, Gavin C. Cawley

CoRR, 2017

Over-Fitting in Model Selection with Gaussian Process Regression.

Rekar O. Mohammed, Gavin C. Cawley

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2017

2015

Benchmarking the semi-supervised naïve Bayes classifier.

Awat A. Saeed, Gavin C. Cawley, Anthony J. Bagnall

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Design of the 2015 ChaLearn AutoML challenge.

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

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014

Kernel learning at the first level of inference.

Gavin C. Cawley, Nicola L. C. Talbot

Neural Networks, 2014

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

Daniel Taylor, Gavin C. Cawley, Steven Hayward

Bioinform., 2014

2012

Over-Fitting in Model Selection and Its Avoidance.

Gavin C. Cawley

Proceedings of the Advances in Intelligent Data Analysis XI - 11th International Symposium, 2012

2011

Results of the Active Learning Challenge.

Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire

Proceedings of the Active Learning and Experimental Design workshop, 2011

Baseline Methods for Active Learning.

Gavin C. Cawley

Proceedings of the Active Learning and Experimental Design workshop, 2011

Sparse Bayesian prediction of disordered residues and disordered regions based on amino-acid composition.

Gavin C. Cawley, Steven Hayward, Gareth J. Janacek, Geoff R. Moore

Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

2010

Model Selection: Beyond the Bayesian/Frequentist Divide.

Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C. Cawley

J. Mach. Learn. Res., 2010

On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation.

Gavin C. Cawley, Nicola L. C. Talbot

J. Mach. Learn. Res., 2010

Design and analysis of the WCCI 2010 active learning challenge.

Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire

Proceedings of the International Joint Conference on Neural Networks, 2010

2008

Analysis of the IJCNN 2007 agnostic learning vs. prior knowledge challenge.

Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C. Cawley

Neural Networks, 2008

Causal and Non-Causal Feature Selection for Ridge Regression.

Gavin C. Cawley

Proceedings of the Causation and Prediction Challenge at WCCI 2008, 2008

Comparing text-driven and speech-driven visual speech synthesisers.

Barry-John Theobald, Gavin C. Cawley, J. Andrew Bangham, Iain A. Matthews, Nicholas Wilkinson

Proceedings of the 9th Annual Conference of the International Speech Communication Association, 2008

2007

An Empirical Evaluation of the Fuzzy Kernel Perceptron.

Gavin C. Cawley

IEEE Trans. Neural Networks, 2007

Optimally regularised kernel Fisher discriminant classification.

Kamel Saadi, Nicola L. C. Talbot, Gavin C. Cawley

Neural Networks, 2007

Predictive uncertainty in environmental modelling.

Gavin C. Cawley, Gareth J. Janacek, Malcolm R. Haylock, Stephen R. Dorling

Neural Networks, 2007

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

Gavin C. Cawley, Nicola L. C. Talbot

J. Mach. Learn. Res., 2007

Super Computer Heterogeneous Classifier Meta-Ensembles.

Anthony J. Bagnall, Gavin C. Cawley, Ian M. Whittley, Larry Bull, Matthew Studley, Mike Pettipher, Firat Tekiner

Int. J. Data Warehous. Min., 2007

Agnostic Learning vs. Prior Knowledge Challenge.

Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C. Cawley

Proceedings of the International Joint Conference on Neural Networks, 2007

Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines.

Gavin C. Cawley, Nicola L. C. Talbot

Proceedings of the International Joint Conference on Neural Networks, 2007

Generalised Kernel Machines.

Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. Talbot

Proceedings of the International Joint Conference on Neural Networks, 2007

Model Selection for Kernel Probit Regression.

Gavin C. Cawley

Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

2006

Sparse bayesian kernel survival analysis for modeling the growth domain of microbial pathogens.

Gavin C. Cawley, Nicola L. C. Talbot, Gareth J. Janacek, Mike W. Peck

IEEE Trans. Neural Networks, 2006

New Issues in Neurocomputing.

Jochen J. Steil, Gavin C. Cawley, Fabrice Rossi

Neurocomputing, 2006

Statistical models to assess the health effects and to forecast ground-level ozone.

Uwe Schlink, Olf Herbarth, Matthias Richter, Stephen R. Dorling, Giuseppe Nunnari, Gavin C. Cawley, Emil Pelikán

Environ. Model. Softw., 2006

Gene selection in cancer classification using sparse logistic regression with Bayesian regularization.

Gavin C. Cawley, Nicola L. C. Talbot

Bioinform., 2006

Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation.

Gavin C. Cawley, Nicola L. C. Talbot, Mark A. Girolami

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Predictive Uncertainty in Environmental Modelling.

Gavin C. Cawley, Malcolm R. Haylock, Stephen R. Dorling

Proceedings of the International Joint Conference on Neural Networks, 2006

Leave-One-Out Cross-Validation Based Model Selection Criteria for Weighted LS-SVMs.

Gavin C. Cawley

Proceedings of the International Joint Conference on Neural Networks, 2006

2005

Constructing Bayesian formulations of sparse kernel learning methods.

Gavin C. Cawley, Nicola L. C. Talbot

Neural Networks, 2005

Trends in Neurocomputing at ESANN 2004.

Jochen J. Steil, Gavin C. Cawley, Thomas Villmann

Neurocomputing, 2005

The evidence framework applied to sparse kernel logistic regression.

Gavin C. Cawley, Nicola L. C. Talbot

Neurocomputing, 2005

Estimating Predictive Variances with Kernel Ridge Regression.

Gavin C. Cawley, Nicola L. C. Talbot, Olivier Chapelle

Proceedings of the Machine Learning Challenges, 2005

sparse Bayesian promoter based gene classification.

Kee Khoon Lee, Gavin C. Cawley, Michael W. Bevan

Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005

2004

Near-videorealistic synthetic talking faces: implementation and evaluation.

Barry-John Theobald, J. Andrew Bangham, Iain A. Matthews, Gavin C. Cawley

Speech Commun., 2004

Fast exact leave-one-out cross-validation of sparse least-squares support vector machines.

Gavin C. Cawley, Nicola L. C. Talbot

Neural Networks, 2004

Heteroscedastic kernel ridge regression.

Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Foxall, Stephen R. Dorling, Danilo P. Mandic

Neurocomputing, 2004

Modelling SO² concentration at a point with statistical approaches.

Giuseppe Nunnari, Stephen R. Dorling, Uwe Schlink, Gavin C. Cawley, Robert J. Foxall, Tim J. Chatterton

Environ. Model. Softw., 2004

Optimally Regularised Kernel Fisher Discriminant Analysis.

Kamel Saadi, Nicola L. C. Talbot, Gavin C. Cawley

Proceedings of the 17th International Conference on Pattern Recognition, 2004

Efficient Model Selection for Kernel Logistic Regression.

Gavin C. Cawley, Nicola L. C. Talbot

Proceedings of the 17th International Conference on Pattern Recognition, 2004

Sparse Bayesian kernel logistic regression.

Gavin C. Cawley, Nicola L. C. Talbot

Proceedings of the 12th European Symposium on Artificial Neural Networks, 2004

Bayesian Kernel Learning Methods for Parametric Accelerated Life Survival Analysis.

Gavin C. Cawley, Nicola L. C. Talbot, Gareth J. Janacek, Michael W. Peck

Proceedings of the Deterministic and Statistical Methods in Machine Learning, 2004

2003

Efficient leave-one-out cross-validation of kernel fisher discriminant classifiers.

Gavin C. Cawley, Nicola L. C. Talbot

Pattern Recognit., 2003

Towards a low bandwidth talking face using appearance models.

Barry-John Theobald, Silko Kruse, J. Andrew Bangham, Gavin C. Cawley

Image Vis. Comput., 2003

The use of confidence measures in vector based call-routing.

Stephen J. Cox, Gavin C. Cawley

Proceedings of the 8th European Conference on Speech Communication and Technology, EUROSPEECH 2003, 2003

Near-videorealistic synthetic visual speech using non-rigid appearance models.

Barry-John Theobald, Gavin C. Cawley, Iain A. Matthews, J. Andrew Bangham

Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression.

Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Foxall, Stephen R. Dorling, Danilo P. Mandic

Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

Efficient cross-validation of kernel fisher discriminant classifiers.

Gavin C. Cawley, Nicola L. C. Talbot

Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

Statistical downscaling with artificial neural networks.

Gavin C. Cawley, Malcolm R. Haylock, Stephen R. Dorling, Clare Goodess, Phil D. Jones

Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

2.5D Visual Speech Synthesis Using Appearance Models.

Barry-John Theobald, J. Andrew Bangham, Iain A. Matthews, John R. W. Glauert, Gavin C. Cawley

Proceedings of the British Machine Vision Conference, 2003

Evaluation of a talking head based on appearance models.

Barry-John Theobald, J. Andrew Bangham, Iain A. Matthews, Gavin C. Cawley

Proceedings of the AVSP 2003, 2003

2002

Reduced Rank Kernel Ridge Regression.

Gavin C. Cawley, Nicola L. C. Talbot

Neural Process. Lett., 2002

Improved sparse least-squares support vector machines.

Gavin C. Cawley, Nicola L. C. Talbot

Neurocomputing, 2002

Towards video realistic synthetic visual speech.

Barry-John Theobald, J. Andrew Bangham, Iain A. Matthews, Gavin C. Cawley

Proceedings of the IEEE International Conference on Acoustics, 2002

Error Functions for Prediction of Episodes of Poor Air Quality.

Robert J. Foxall, Gavin C. Cawley, Stephen R. Dorling, Danilo P. Mandic

Proceedings of the Artificial Neural Networks, 2002

A Greedy Training Algorithm for Sparse Least-Squares Support Vector Machines.

Gavin C. Cawley, Nicola L. C. Talbot

Proceedings of the Artificial Neural Networks, 2002

Fast exact leave-one-out cross-validation of least-squares Support Vector Machines.

Kamel Saadi, Gavin C. Cawley, Nicola L. C. Talbot

Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

Heteroscedastic regularised kernel regression for prediction of episodes of poor air quality.

Robert J. Foxall, Gavin C. Cawley, Nicola L. C. Talbot, Stephen R. Dorling, Danilo P. Mandic

Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

Efficient formation of a basis in a kernel induced feature space.

Gavin C. Cawley, Nicola L. C. Talbot

Proceedings of the 10th Eurorean Symposium on Artificial Neural Networks, 2002

Non-retrieval: Blocking Pornographic Images.

Alison Bosson, Gavin C. Cawley, Yi Chan, Richard W. Harvey

Proceedings of the Image and Video Retrieval, International Conference, 2002

2001

Simplified implementation of the recursive median sieve.

Olli Yli-Harja, Pertti Koivisto, J. Andrew Bangham, Gavin C. Cawley, Richard W. Harvey, Ilya Shmulevich

Signal Process., 2001

Nonlinear modelling of air pollution time series.

Robert J. Foxall, Igor R. Krcmar, Gavin C. Cawley, Stephen R. Dorling, Danilo P. Mandic

Proceedings of the IEEE International Conference on Acoustics, 2001

Visual speech synthesis using statistical models of shape and appearance.

Barry-John Theobald, J. Andrew Bangham, Iain A. Matthews, Gavin C. Cawley

Proceedings of the Auditory-Visual Speech Processing, 2001

2000

On a Fast, Compact Approximation of the Exponential Function.

Gavin C. Cawley

Neural Comput., 2000

1998

The Segmentation of Images via Scale-Space Trees.

J. Andrew Bangham, Javier Ruiz Hidalgo, Richard W. Harvey, Gavin C. Cawley

Proceedings of the British Machine Vision Conference 1998, 1998

1997

Speech coding and synthesis using parametric curves.

Luis Miguel Teixeira de Jesus, Gavin C. Cawley

Proceedings of the Fifth European Conference on Speech Communication and Technology, 1997

A Fast Index Assignment Method for Robust Vector Quantization of Image Data.

Nicola L. C. Talbot, Gavin C. Cawley

Proceedings of the Proceedings 1997 International Conference on Image Processing, 1997

1996

An improved vector quantization algorithm for speech transmission over noisy channels.

Gavin C. Cawley

Proceedings of the 4th International Conference on Spoken Language Processing, 1996

Reproducing a Subjective Classification Scheme for Atmospheric Circulation Patterns over the United Kingdom Using a Neural Network.

Gavin C. Cawley, Stephen R. Dorling

Proceedings of the Artificial Neural Networks, 1996