D. M. Titterington

According to our database1, D. M. Titterington authored at least 45 papers between 1984 and 2016.

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Bibliography

2016
Transdimensional sequential Monte Carlo using variational Bayes - SMCVB.
Computational Statistics & Data Analysis, 2016

2011
t -Tests, F -Tests and Otsu's Methods for Image Thresholding.
IEEE Trans. Image Processing, 2011

Median-based image thresholding.
Image Vision Comput., 2011

2010
Joint discriminative-generative modelling based on statistical tests for classification.
Pattern Recognition Letters, 2010

Preface.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

On the generative-discriminative tradeoff approach: Interpretation, asymptotic efficiency and classification performance.
Computational Statistics & Data Analysis, 2010

2009
Variational Bayes for estimating the parameters of a hidden Potts model.
Statistics and Computing, 2009

Interpretation of hybrid generative/discriminative algorithms.
Neurocomputing, 2009

2008
Short note on two output-dependent hidden Markov models.
Pattern Recognition Letters, 2008

Do unbalanced data have a negative effect on LDA?
Pattern Recognition, 2008

Comment on "On Discriminative vs. Generative Classifiers: A Comparison of Logistic Regression and Naive Bayes".
Neural Processing Letters, 2008

2007
Variational approximations in Bayesian model selection for finite mixture distributions.
Computational Statistics & Data Analysis, 2007

Kernel ellipsoidal trimming.
Computational Statistics & Data Analysis, 2007

2006
The Minimum Volume Covering Ellipsoid Estimation in Kernel-Defined Feature Spaces.
Proceedings of the Machine Learning: ECML 2006, 2006

2005
Hierarchical Gaussian process mixtures for regression.
Statistics and Computing, 2005

Some Aspects of Latent Structure Analysis.
Proceedings of the Subspace, 2005

Inadequacy of interval estimates corresponding to variational Bayesian approximations.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Lack of Consistency of Mean Field and Variational break Bayes Approximations for State Space Models.
Neural Processing Letters, 2004

Convergence and Asymptotic Normality of Variational Bayesian Approximations for Expon.
Proceedings of the UAI '04, 2004

Probabilistic Image Processing based on the Q-Ising Model by Means of the Mean-Field Method and Loopy Belief Propagation.
Proceedings of the 17th International Conference on Pattern Recognition, 2004

Variational Bayes Estimation of Mixing Coefficients.
Proceedings of the Deterministic and Statistical Methods in Machine Learning, 2004

2003
Mixtures of Factor Analysers. Bayesian Estimation and Inference by Stochastic Simulation.
Machine Learning, 2003

Loopy belief propagation and probabilistic image processing.
Proceedings of the NNSP 2003, 2003

Filtered Gaussian Processes for Learning with Large Data-Sets.
Proceedings of the Switching and Learning in Feedback Systems, 2003

2000
Statistics and Neural Networks.
Technometrics, 2000

Improving the Mean-Field Approximation in Belief Networks Using Bahadur's Reparameterisation of the Multivariate Binary Distribution.
Neural Processing Letters, 2000

1999
Discussion on the paper by Friedman and Fisher.
Statistics and Computing, 1999

On perfect simulation for some mixtures of distributions.
Statistics and Computing, 1999

Modelling magnetic material images with simultaneous autoregressions.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

The exploration of new methods for learning in binary Boltzmann machines.
Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

1998
Reparameterization strategies for hidden Markov models and Bayesian approaches to maximum likelihood estimation.
Statistics and Computing, 1998

Mean fields and two-dimensional Markov random fields in image analysis.
Pattern Anal. Appl., 1998

1997
On the shrinkage of local linear curve estimators.
Statistics and Computing, 1997

Computational Bayesian Analysis of Hidden Markov Mesh Models.
IEEE Trans. Pattern Anal. Mach. Intell., 1997

1996
On a Modification to the Mean Field EM Algorithm in Factorial Learning.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

1995
Beyond the binary Boltzmann machine.
IEEE Trans. Neural Networks, 1995

On some Bayesian/regularization methods for image restoration.
IEEE Trans. Image Processing, 1995

1994
An Empirical Study of the Simulation of Various Models used for Images.
IEEE Trans. Pattern Anal. Mach. Intell., 1994

1993
Bayesian Image Restoration: An Application to Edge-Preserving Surface Recovery.
IEEE Trans. Pattern Anal. Mach. Intell., 1993

1992
On the estimation of noisy binary Markov random fields.
Pattern Recognition, 1992

1991
Pixel labelling for three-dimensional scenes based on Markov mesh models.
Signal Processing, 1991

A Study of Methods of Choosing the Smoothing Parameter in Image Restoration by Regularization.
IEEE Trans. Pattern Anal. Mach. Intell., 1991

1989
An alternative stochastic supervisor in discriminant analysis.
Pattern Recognition, 1989

1987
A Re-Examination of the Distance-Weighted k-Nearest Neighbor Classification Rule.
IEEE Trans. Systems, Man, and Cybernetics, 1987

1984
Comments on "Application of the Conditional Population-Mixture Model to Image Segmentation".
IEEE Trans. Pattern Anal. Mach. Intell., 1984


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