Nicola L. C. Talbot - researchr alias

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Viewing Publication 1 - 28 from 28

2014

Kernel learning at the first level of inferenceGavin C. Cawley, Nicola L. C. Talbot. NN, 53:69-80, 2014. [doi]

2010

On Over-fitting in Model Selection and Subsequent Selection Bias in Performance EvaluationGavin C. Cawley, Nicola L. C. Talbot. jmlr, 11:2079-2107, 2010. [doi]

2007

2006

Sparse bayesian kernel survival analysis for modeling the growth domain of microbial pathogensGavin C. Cawley, Nicola L. C. Talbot, Gareth J. Janacek, Mike W. Peck. tnn, 17(2):471-481, 2006. [doi]

Gene selection in cancer classification using sparse logistic regression with Bayesian regularizationGavin C. Cawley, Nicola L. C. Talbot. bioinformatics, 22(19):2348-2355, 2006. [doi]

Sparse Multinomial Logistic Regression via Bayesian L1 RegularisationGavin C. Cawley, Nicola L. C. Talbot, Mark Girolami. nips 2007: 209-216 [doi]

2005

Estimating Predictive Variances with Kernel Ridge RegressionGavin C. Cawley, Nicola L. C. Talbot, Olivier Chapelle. mlcw 2006: 56-77 [doi]

The evidence framework applied to sparse kernel logistic regressionGavin C. Cawley, Nicola L. C. Talbot. ijon, 64:119-135, 2005. [doi]

Constructing Bayesian formulations of sparse kernel learning methodsGavin C. Cawley, Nicola L. C. Talbot. NN, 18(5-6):674-683, 2005. [doi]

2004

Bayesian Kernel Learning Methods for Parametric Accelerated Life Survival AnalysisGavin C. Cawley, Nicola L. C. Talbot, Gareth J. Janacek, Michael Peck. dsmml 2005: 37-55 [doi]

Sparse Bayesian kernel logistic regressionGavin C. Cawley, Nicola L. C. Talbot. esann 2004: 133-138 [doi]

Efficient Model Selection for Kernel Logistic RegressionGavin C. Cawley, Nicola L. C. Talbot. icpr 2004: 439-442 [doi]

Fast exact leave-one-out cross-validation of sparse least-squares support vector machinesGavin C. Cawley, Nicola L. C. Talbot. NN, 17(10):1467-1475, 2004. [doi]

Heteroscedastic kernel ridge regressionGavin C. Cawley, Nicola L. C. Talbot, Robert J. Foxall, Stephen R. Dorling, Danilo P. Mandic. ijon, 57:105-124, 2004. [doi]

Optimally Regularised Kernel Fisher Discriminant AnalysisKamel Saadi, Nicola L. C. Talbot, Gavin C. Cawley. icpr 2004: 427-430 [doi]

2003

Efficient cross-validation of kernel fisher discriminant classifiersGavin C. Cawley, Nicola L. C. Talbot. esann 2003: 241-246 [doi]

Efficient leave-one-out cross-validation of kernel fisher discriminant classifiersGavin C. Cawley, Nicola L. C. Talbot. PR, 36(11):2585-2592, 2003. [doi]

Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regressionGavin C. Cawley, Nicola L. C. Talbot, Robert J. Foxall, Stephen R. Dorling, Danilo P. Mandic. esann 2003: 209-214 [doi]

2002

Reduced Rank Kernel Ridge RegressionGavin C. Cawley, Nicola L. C. Talbot. npl, 16(3):293-302, 2002.

Improved sparse least-squares support vector machinesGavin C. Cawley, Nicola L. C. Talbot. ijon, 48(1-4):1025-1031, 2002. [doi]

Efficient formation of a basis in a kernel induced feature spaceGavin C. Cawley, Nicola L. C. Talbot. esann 2002: 1-6

A Greedy Training Algorithm for Sparse Least-Squares Support Vector MachinesGavin C. Cawley, Nicola L. C. Talbot. icann 2002: 681-686 [doi]

Heteroscedastic regularised kernel regression for prediction of episodes of poor air qualityRobert J. Foxall, Gavin C. Cawley, Nicola L. C. Talbot, Stephen R. Dorling, Danilo P. Mandic. esann 2002: 19-24

Fast exact leave-one-out cross-validation of least-squares Support Vector MachinesKamel Saadi, Gavin C. Cawley, Nicola L. C. Talbot. esann 2002: 149-154

1997

A Fast Index Assignment Method for Robust Vector Quantization of Image DataNicola L. C. Talbot, Gavin C. Cawley. icip 1997: 674-677 [doi]

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