Workshop in Statistical Mixtures and
Latent-Structure Modelling

28-30 March 2001

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Scientific Programme

[See also the Organisers' site here for more detailed scientific information.]


A provisional timetable with titles of talks is given below.
M. Aitkin
(Newcastle, UK)
G. Hinton
C.P. Robert
(Paris Dauphine, France)
C. Andrieu
(Bristol, UK)
B.G. Lindsay
(Penn State, USA)
G.O. Roberts
(Lancaster, UK)
C.M. Bishop
(Microsoft, UK)
N.L. Hjort
(Oslo, Norway)
T. Ryden
(Lund, Sweden)
G. Celeux
(INRIA, France)
D.J.C. MacKay
(Cambridge, UK)
C. Skinner
(Southampton, UK)
P. Dellaportas
(Athens, Greece)
G.J. McLachlan
(Queensland, Australia)
M. Stephens
(Washington, USA)
E. Gassiat
(Orsay, France)
E. Moulines
(ENST Paris, France)
M. Titterington
(Glasgow, UK)
P.J. Green
(Bristol, IK)
R. Neal
(Toronto, Canada)
C.K.I. Williams
(Edinburgh, UK)

Provisional Programme and Titles

Wednesday 28 March
0900 - 1000 Registration
1000 - 1100 C. P. Robert Overview -Where do we stand on mixtures?
1100 - 1130 Coffee
1130 - 1250 M. Aitkin A general mixture ML analysis for random effect models
C. Skinner Estimation of distributions in the presence of measurement error
1250 - 1420 Lunch
1420 - 1540 M. Stephens Inferring latent population structure from genetic data
P.J. Green Mixtures in time and space
1540 - 1610 Tea
1610 - 1730 P. Dellaportas Latent variables for modelling volatility processes
G. O. Roberts Bayesian inference for discretely observed diffusion processes
1730 - 1900 Wine and Cheese reception
Thursday 29 March
0930 - 1045 N.L. Hjort On attempts at generalising the Dirichlet process
B. Garel Likelihood ratio test for univariate Gaussian mixture
Posters 1-6 Spotlights
1045 - 1115 Coffee
1115 - 1235 C.M. Bishop Variational methods and latent variables
R. M. Neal Why we should not use the galaxy data
Posters 7-12 Spotlights
1235 - 1400 Lunch
1400 - 1600 R. Neal Hierarchical mixtures using diffusion tree priors
C.K.I. Williams Image modelling with dynamic trees
D. J. C. MacKay The state of the art in error correcting codes
1600 - 1630 Tea
1615 - 1800 Poster Session
1930 Optional dinner
Friday 30 March
0930 - 1050 G.J. McLachlan On the incremental EM Algorithm for speeding up the fitting of finite mixture models
C. Andrieu SAME, SA²ME, FAME and RDA
1050 - 1120 Coffee
1120 - 1240 E. Gassiat The number of populations in a mixture with Markov regime
B.G. Lindsay On determining an adequate number of mixture components
1240 - 1400 Lunch
1400 - 1520 T. Ryden Continuous-time jump MCMC and model selection for HMMs
G. Celeux Assessing the number of mixture components: a survey
1520 - 1540 Tea
1540 - 1630 M. Titterington Summing up


  1. Brendan Murphy - Mixture models for ranking data
  2. C. Glasbey - Time series and spatial models for solar radiation
  3. S Richardson, L Leblond, I Jaussent and P.J Green - Mixture models in measurement error problems
  4. M. Fatima Salgueiro, John W. McDonald and Peter W.F. Smith - The observed association structure from graphical Gaussian models with a single latent variable
  5. Matthias Seeger - Covariance kernels from Bayesian generative models
  6. Jenny Mooney - Using mixtures of von Mises distributions to model seasonality in sudden infant death syndrome
  7. Matthew J. Beal and Zoubin Ghahramani - Variational inference for Bayesian structure learning
  8. Kerrie Mengersen - Phase randomisation as a convergence tool in MCMC.
  9. P.Besbeas and B.J.T.Morgan - Integrated squared error estimation of normal mixture parameters
  10. Carl Edward Rasmussen - Dirichlet process mixture models
  11. Agostino Nobile - Constraints on the posterior distribution of a finite mixture
  12. Colin Aitken - Sequential analysis of mixtures of discrete items
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