Workshop in Statistical Mixtures and
Latent-Structure Modelling
28-30 March 2001
Scientific Programme
[See also the Organisers' site here for more detailed scientific information.]Speakers
A provisional timetable with titles of talks is given below.| M. Aitkin (Newcastle, UK) |
G. Hinton (UCL, UK) |
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 |
Posters
- Brendan Murphy - Mixture models for ranking data
- C. Glasbey - Time series and spatial models for solar radiation
- S Richardson, L Leblond, I Jaussent and P.J Green - Mixture models in measurement error problems
- M. Fatima Salgueiro, John W. McDonald and Peter W.F. Smith - The observed association structure from graphical Gaussian models with a single latent variable
- Matthias Seeger - Covariance kernels from Bayesian generative models
- Jenny Mooney - Using mixtures of von Mises distributions to model seasonality in sudden infant death syndrome
- Matthew J. Beal and Zoubin Ghahramani - Variational inference for Bayesian structure learning
- Kerrie Mengersen - Phase randomisation as a convergence tool in MCMC.
- P.Besbeas and B.J.T.Morgan - Integrated squared error estimation of normal mixture parameters
- Carl Edward Rasmussen - Dirichlet process mixture models
- Agostino Nobile - Constraints on the posterior distribution of a finite mixture
- Colin Aitken - Sequential analysis of mixtures of discrete items