Gavin C. Cawley

Gavin C. Cawley, Stephen R. Dorling, Danilo P. Mandic, 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

Results of the Active Learning Challenge

Isabelle Guyon, Gavin C. Cawley, Vincent Lemaire, 2011, Active Learning and Experimental Design @ AISTATS.

Modelling SO2 concentration at a point with statistical approaches

Gavin C. Cawley, Stephen R. Dorling, Giuseppe Nunnari, 2004, Environ. Model. Softw..

Machine Learning and Data Mining in Pattern Recognition

Gavin C. Cawley, Rekar O. Mohammed, Petra Perner, 2017, Lecture Notes in Computer Science.

An improved vector quantization algorithm for speech transmission over noisy channels

Gavin C. Cawley, G. Cawley, 1996, ICSLP.

Agnostic Learning vs. Prior Knowledge Challenge

Isabelle Guyon, Gavin C. Cawley, Gideon Dror, 2007, 2007 International Joint Conference on Neural Networks.

Maximum likelihood cost functions for neural network models of air quality data

Gavin C. Cawley, Danilo P. Mandic, Stephen Dorling, 2003 .

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

Gavin C. Cawley, Barry-John Theobald, Iain A. Matthews, 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

A simple trick for constructing Bayesian formulations of sparse kernel learning methods

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

A fast index assignment method for robust vector quantisation of image data

Gavin C. Cawley, Nicola L. C. Talbot, 1997, Proceedings of International Conference on Image Processing.

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

Gavin C. Cawley, Anthony J. Bagnall, G. Cawley, 2017, ArXiv.

Pattern recognition with the decomposed multilayer perceptron

Simon M. Lucas, Gavin C. Cawley, P. D. Noakes, 1993 .

An Empirical Evaluation of the Fuzzy Kernel Perceptron

Gavin C. Cawley, 2007, IEEE Transactions on Neural Networks.

Generalised Kernel Machines

Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. Talbot, 2007, 2007 International Joint Conference on Neural Networks.

Fast Method of Channel Equalisation for Speech Signals and its Implementation on a DSP

Gavin C. Cawley, Stephen Cox, Ben Milner, 1999 .

Baseline Methods for Active Learning

Gavin C. Cawley, G. Cawley, 2011, Active Learning and Experimental Design @ AISTATS.

Towards a low bandwidth talking face using appearance models

Gavin C. Cawley, Barry-John Theobald, Silko Kruse, 2003, Image Vis. Comput..

Allophone Synthesis Using A Neural Network

Gavin C. Cawley, P. D. Noakes, 1992 .

Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation

Gavin C. Cawley, Mark A. Girolami, Nicola L. C. Talbot, 2006, NIPS.

of the 2015 ChaLeam AutoML Challenge

Isabelle Guyon, Gavin C. Cawley, Hugo Jair Escalante, 2015 .

Design and analysis of the WCCI 2010 active learning challenge

Isabelle Guyon, Gavin C. Cawley, Vincent Lemaire, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Estimating Predictive Variances with Kernel Ridge Regression

Gavin C. Cawley, Nicola L. C. Talbot, Olivier Chapelle, 2005, MLCW.

Causal and Non-Causal Feature Selection for Ridge Regression

Gavin C. Cawley, G. Cawley, 2008, WCCI Causation and Prediction Challenge.

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

Gavin C. Cawley, Michael Flynn, James Large, 2018, ArXiv.

Over-Fitting in Model Selection and Its Avoidance

Gavin C. Cawley, G. Cawley, 2012, IDA.

Non-retrieval: Blocking Pornographic Images

Gavin C. Cawley, Yi Chan, Richard Harvey, 2002, CIVR.

Manipulation of prior probabilities in support vector classification

Gavin C. Cawley, Nicola L. C. Talbot, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

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

Gavin C. Cawley, James Large, Anthony J. Bagnall, 2020, ECML/PKDD.

Optimally regularised kernel Fisher discriminant classification

Gavin C. Cawley, Kamel Saadi, Nicola L. C. Talbot, 2007, Neural Networks.

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

Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. Talbot, 2006, IEEE Transactions on Neural Networks.

Visual speech synthesis using statistical models of shape and appearance

Gavin C. Cawley, Barry-John Theobald, Iain A. Matthews, 2001, AVSP.

Speech coding and synthesis using parametric curves

Gavin C. Cawley, Luis M. T. Jesus, Luis Miguel Teixeira de Jesus, 1997, EUROSPEECH.

Comparing text-driven and speech-driven visual speech synthesisers

Gavin C. Cawley, Barry-John Theobald, Nicholas Wilkinson, 2008, INTERSPEECH.

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

Gavin C. Cawley, Stephen R. Dorling, Danilo P. Mandic, 2002, The European Symposium on Artificial Neural Networks.

Reconstruction of sub-surface archaeological remains from magnetic data using neural computing.

Gavin C. Cawley, David Bescoby, P. N. Chroston, 2003 .

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

Gavin C. Cawley, Steven Hayward, Daniel Taylor, 2014, Bioinform..

Error Functions for Prediction of Episodes of Poor Air Quality

Gavin C. Cawley, Stephen R. Dorling, Danilo P. Mandic, 2002, ICANN.

On a Fast, Compact Approximation of the Exponential Function

Gavin C. Cawley, G. Cawley, 2000, Neural Computation.

Interpretation of geophysical surveys of archaeological sites using artificial neural networks

Gavin C. Cawley, P. N. Chroston, D. J. Bescoby, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

The application of neural networks to cognitive phonetic modelling

Gavin C. Cawley, A.D.P. Green, 1991 .

Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2007, 2007 International Joint Conference on Neural Networks.

An improved vector quantisation algorithm for speech transmission over noisy channels

Gavin C. Cawley, 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

E-cient Cross-Validationof Kernel FisherDiscriminant Classiflers

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2003 .

The Segmentation of Images via Scale-Space Trees

Gavin C. Cawley, Javier Ruiz Hidalgo, J. Andrew Bangham, 1998, BMVC.

Simplified implementation of the recursive median sieve

Gavin C. Cawley, Pertti Koivisto, Ilya Shmulevich, 2001, Signal Process..

Towards a low bandwidth talking face using appearance models

Gavin C. Cawley, Barry-John Theobald, Silko Kruse, 2003, Image Vis. Comput..

Super Computer Heterogeneous Classifier Meta-Ensembles

Gavin C. Cawley, Larry Bull, Matthew Studley, 2007, Int. J. Data Warehous. Min..

Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression

Gavin C. Cawley, Stephen R. Dorling, Danilo P. Mandic, 2003, ESANN.

Hands-On Pattern Recognition: Challenges in Machine Learning, volume 1

Gavin C. Cawley, Gideon Dror, Isabelle Guyon, 2011 .

Efficient cross-validation of kernel fisher discriminant classifiers

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2003, ESANN.

Inter-comparison of neural network, statistical and deterministic models for predicting the concentrations of NO2 and PM10 in urban air

Gavin C. Cawley, Mikko Kolehmainen, Ari Karppinen, 2003 .

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

Gavin C. Cawley, G. Cawley, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Evaluation of a talking head based on appearance models

Gavin C. Cawley, Barry-John Theobald, Iain A. Matthews, 2003, AVSP.

Efficient formation of a basis in a kernel induced feature space

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2002, ESANN.

The use of vector quantization in neural speech synthesis

Gavin C. Cawley, P. D. Noakes, 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

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

Isabelle Guyon, Gavin C. Cawley, Gideon Dror, 2008, Neural Networks.

Model Selection for Kernel Probit Regression

Gavin C. Cawley, G. Cawley, 2007, ESANN.

Efficient model selection for kernel logistic regression

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

Benchmarking the semi-supervised naïve Bayes classifier

Gavin C. Cawley, Anthony J. Bagnall, Awat A. Saeed, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

The use of confidence measures in vector based call-routing

Gavin C. Cawley, Stephen J. Cox, 2003, INTERSPEECH.

On decomposing MLPs

Simon M. Lucas, Gavin C. Cawley, P. D. Noakes, 1993, IEEE International Conference on Neural Networks.

The Application of Neural Networks to Phonetic Modelling

Gavin C. Cawley, G. Cawley, 1996 .

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

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2003, Pattern Recognit..

Near-videorealistic synthetic talking faces: implementation and evaluation

Gavin C. Cawley, Barry-John Theobald, Iain A. Matthews, 2004, Speech Commun..

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

Gavin C. Cawley, Gareth J. Janacek, Steven Hayward, 2011, The 2011 International Joint Conference on Neural Networks.

Trends in Neurocomputing at ESANN 2004

Thomas Villmann, Gavin C. Cawley, Jochen J. Steil, 2005, Neurocomputing.

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

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2007, J. Mach. Learn. Res..

Empirical Evaluation of Resampling Procedures for Optimising SVM Hyperparameters

Jacques Wainer, Gavin C. Cawley, G. Cawley, 2017, J. Mach. Learn. Res..

Model Selection: Beyond the Bayesian/Frequentist Divide

Isabelle Guyon, Gavin C. Cawley, Gideon Dror, 2010, J. Mach. Learn. Res..

Train-spotting: building classifiers for microarrays

Gavin C. Cawley, Yuxuan Lan, Richard J. Harvey, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

Gene Selection in Cancer Classification using Sparse Logistic Regression with Bayesian Regularisation

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2006 .

CLOP: a Matlab Learning Object Package

Isabelle Guyon, Gavin C. Cawley, Hugo Jair Escalante, 2007 .

Predictive Uncertainty in Environmental Modelling

Gavin C. Cawley, Malcolm R. Haylock, Stephen R. Dorling, 2006, IJCNN.

Reduced Rank Kernel Ridge Regression

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2002, Neural Processing Letters.

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

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2010, J. Mach. Learn. Res..

Kernel learning at the first level of inference

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2014, Neural Networks.

Improved sparse least-squares support vector machines

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2002, Neurocomputing.

Optimally regularised kernel Fisher discriminant analysis

Gavin C. Cawley, Kamel Saadi, Nicola L. C. Talbot, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

Optimally regularised kernel Fisher discriminant analysis

Gavin C. Cawley, Kamel Saadi, Nicola L. C. Talbot, 2004, ICPR 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

Gavin C. Cawley, Mikko Kolehmainen, Ari Karppinen, 2003 .

A rigorous inter-comparison of ground-level ozone predictions

Gavin C. Cawley, Mikko Kolehmainen, Emil Pelikán, 2003 .

Predictive Uncertainty in Environmental Modelling 1 Predictive Uncertainty in Environmental Modelling

Gavin C. Cawley, Gareth J. Janacek, G. Cawley, 2007 .

A simple trick for constructing Bayesian formulations of sparse kernel learning methods

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 2005 .

Evaluation of neural network, statistical and deterministic models against the measured concentrations of NO2, PM10 and PM2.5 in an urban area

Gavin C. Cawley, Danilo P. Mandic, Mikko Kolehmainen, 2002 .

Air Pollution Episodes: Modelling Tools For Improved Smog Management(APPETISE)

Gavin C. Cawley, Mikko Kolehmainen, Ari Karppinen, 2000 .

Fast index assignment algorithm for vector quantisation over noisy transmission channels

Gavin C. Cawley, Nicola L. C. Talbot, G. Cawley, 1996 .

STAtistical and Regional dynamical Downscaling of EXtremes for European regions: some results from the STARDEX project

Gavin C. Cawley, András Bárdossy, Christina Anagnostopoulou, 2003 .