Nicola L. C. Talbot

2007
25	EE	Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. Talbot: Generalised Kernel Machines. IJCNN 2007: 1720-1725
24	EE	Gavin C. Cawley, Nicola L. C. Talbot: Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines. IJCNN 2007: 1732-1737
23	EE	Kamel Saadi, Nicola L. C. Talbot, Gavin C. Cawley: Optimally regularised kernel Fisher discriminant classification. Neural Networks 20(7): 832-841 (2007)
2006
22	EE	Gavin C. Cawley, Nicola L. C. Talbot, Mark Girolami: Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation. NIPS 2006: 209-216
21	EE	Gavin C. Cawley, Nicola L. C. Talbot: Gene selection in cancer classification using sparse logistic regression with Bayesian regularization. Bioinformatics 22(19): 2348-2355 (2006)
20	EE	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 Transactions on Neural Networks 17(2): 471-481 (2006)
2005
19	EE	Gavin C. Cawley, Nicola L. C. Talbot, Olivier Chapelle: Estimating Predictive Variances with Kernel Ridge Regression. MLCW 2005: 56-77
18	EE	Gavin C. Cawley, Nicola L. C. Talbot: Constructing Bayesian formulations of sparse kernel learning methods. Neural Networks 18(5-6): 674-683 (2005)
17	EE	Gavin C. Cawley, Nicola L. C. Talbot: The evidence framework applied to sparse kernel logistic regression. Neurocomputing 64: 119-135 (2005)
2004
16	EE	Gavin C. Cawley, Nicola L. C. Talbot, Gareth J. Janacek, Michael Peck: Bayesian Kernel Learning Methods for Parametric Accelerated Life Survival Analysis. Deterministic and Statistical Methods in Machine Learning 2004: 37-55
15	EE	Gavin C. Cawley, Nicola L. C. Talbot: Sparse Bayesian kernel logistic regression. ESANN 2004: 133-138
14	EE	Kamel Saadi, Nicola L. C. Talbot, Gavin C. Cawley: Optimally Regularised Kernel Fisher Discriminant Analysis. ICPR (2) 2004: 427-430
13	EE	Gavin C. Cawley, Nicola L. C. Talbot: Efficient Model Selection for Kernel Logistic Regression. ICPR (2) 2004: 439-442
12	EE	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): 1467-1475 (2004)
11	EE	Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Foxall, Stephen R. Dorling, Danilo P. Mandic: Heteroscedastic kernel ridge regression. Neurocomputing 57: 105-124 (2004)
2003
10	EE	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: 209-214
9	EE	Gavin C. Cawley, Nicola L. C. Talbot: Efficient cross-validation of kernel fisher discriminant classifiers. ESANN 2003: 241-246
8	EE	Gavin C. Cawley, Nicola L. C. Talbot: Efficient leave-one-out cross-validation of kernel fisher discriminant classifiers. Pattern Recognition 36(11): 2585-2592 (2003)
2002
7		Gavin C. Cawley, Nicola L. C. Talbot: Efficient formation of a basis in a kernel induced feature space. ESANN 2002: 1-6
6		Kamel Saadi, Gavin C. Cawley, Nicola L. C. Talbot: Fast exact leave-one-out cross-validation of least-squares Support Vector Machines. ESANN 2002: 149-154
5		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: 19-24
4	EE	Gavin C. Cawley, Nicola L. C. Talbot: A Greedy Training Algorithm for Sparse Least-Squares Support Vector Machines. ICANN 2002: 681-686
3		Gavin C. Cawley, Nicola L. C. Talbot: Reduced Rank Kernel Ridge Regression. Neural Processing Letters 16(3): 293-302 (2002)
2	EE	Gavin C. Cawley, Nicola L. C. Talbot: Improved sparse least-squares support vector machines. Neurocomputing 48(1-4): 1025-1031 (2002)
1997
1	EE	Nicola L. C. Talbot, Gavin C. Cawley: A Fast Index Assignment Method for Robust Vector Quantization of Image Data. ICIP (3) 1997: 674-677

Coauthor Index

1	Gavin C. Cawley	[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25]
2	Olivier Chapelle	[19]
3	Stephen R. Dorling	[5] [10] [11]
4	Robert J. Foxall	[5] [10] [11]
5	Mark A. Girolami (Mark Girolami)	[22]
6	Gareth J. Janacek	[16] [20] [25]
7	Danilo P. Mandic	[5] [10] [11]
8	Michael Peck	[16]
9	Mike W. Peck	[20]
10	Kamel Saadi	[6] [14] [23]