Nicola L. C. Talbot

According to our database, Nicola L. C. Talbot authored at least 28 papers between 1997 and 2014.

Collaborative distances:

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

2014

Kernel learning at the first level of inference.

Gavin C. Cawley, Nicola L. C. Talbot

Neural Networks, 2014

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

2007

Optimally regularised kernel Fisher discriminant classification.

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

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

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

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

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

2005

Constructing Bayesian formulations of sparse kernel learning methods.

Gavin C. Cawley, Nicola L. C. Talbot

Neural Networks, 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

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

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

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

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

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

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