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Optimisation of MCMC Algorithms Workshop


Organisers: Profressor Gareth Roberts and Dr Natesh Pillai


Programme

Tuesday A1.01
 
1.30 Andrew Stuart
Scaling of MCMC algorithms
 
2.15 Chris Sherlock
Optimal scaling of the random walk Metropolis - generalising the set of targets for which the “0.234” rule applies
 
3.30 Jim Hobert
Improving the Data Augmentation Algorithm
 
4.15 Yves Atchade
A computational framework for empirical Bayes inference
 
 
 
Wednesday AM MS.01
 
9.30 Eric Moulines
Fluid Limit with applications to MCMC algorithms
 
10.15 Galin Jones
Variable-at-a-time Markov Chain Monte Carlo
 
11.30 Peter Neal
Optimal Scaling of random walk Metropolis algorithms with non-Gaussian proposals
 
12.15 Gareth Roberts
Scaling for simulated tempering and MCMCMC
 
 
 
Wednesday PM MS.02
 
2.30 Gersende Fort
Adaptive MCMC : theory and methods
 
 
3.15 Dawn Woodward
Lower Bounds on the Mixing Time of Adaptive MCMC Methods
 
4.15 Heikki Haario
TBA
 
 
Thursday A1.01
 
9.30 Christophe Andrieu
TBA
 
10.15 Alex Beskos
Optimal Tuning for the Hybrid Monte-Carlo Algorithm
 
11.15 Mylene Bedard
On the Optimal Scaling Problem for Hierarchical Target Distributions
 
12.00 Natesh Pillai
Optimal scaling and SPDE limits for non iid targets