May 13 Sunday

8:00-8:45

Breakfast, onsite registration (Harvard Hall 104)

8:45-9:00

Jun Liu

Opening Remark

Plenary Session (Harvard Hall 104)

9:00-9:45

Don Rubin

Applying MCMC to a Classic Problem in Statistics: Estimating dose-response when only treatment versus placebo is randomized -- the Efron-Feldman (1991 JASA) data reanalyzed

9:45-10:30

Nicholas Polson

Optimal Filtering of Jump-Diffusions: Extracting Latent States from Asset Prices

Break

 

Parallel Sessions

 

Session A (Harvard Hall 103)

Session B (Harvard Hall 102)

10:50-11:30

Jie Liang

Transition state ensemble of protein folding and evolutionary selection pressure through Sequential Monte Carlo and MCMC

Jim Fill

A (Minor) Miracle: Diagonalization of a Bose-Einstein Markov Chain

 

11:30-12:10

Ulrich H.E. Hansmann

In Silico Folding of Small Proteins

Christian Robert

A Bayesian reassessment of k-nearest-neighbour classification

 

Lunch (Harvard Hall 104)

 

1:30-2:10

Hongyu Zhao

Bayesian Methods to Infer Protein Interactions

Xiao-Li Meng

Statistical Physics and Statistical Computing: a Critical Link

 

2:10-2:50

Shane T. Jensen

Bayesian Clustering with the Dirichlet Process

David van Dyk

Implementing Gibbs-Type Samplers Using Incompatible Draws With Applications in High-Energy Astrophysics

2:50-3:30

Yves Atchade

The Wang-Landau algorithm: Applications and some convergence results

Xiaodong Wang

Joint Multiple Target Tracking and Classification in Collaborative Sensor

Networks

Coffee Break

 

3:50-4:30

Nancy Zhang

Bayesian Variable Selection in Structured High Dimensional
Covariate Spaces

Murali Haran

Experiments with Monte Carlo methods for spatial models

4:30-5:10

Ming-Hui Chen

Objective Bayesian Variable Selection for Logistic Regression Models with Jeffreys's Prior

Arnaud Doucet

Particle Markov Chain Monte Carlo

6:00-7:00

H'ours Oeuvres (Sheraton Commander Hotel)

6:00-9:00

Banquet (Sheraton Commander Hotel)

6:00-11:00

Poster session (Sheraton Commander Hotel)

 

May 14 Monday

8:00-9:00

Breakfast (Harvard Hall 104)

Plenary Session

9:00-9:45

David Landau

A new approach to Monte Carlo sampling in statistical physics and beyond

9:45-10:30

Andrew Gelman

Weakly informative priors

10:30-11:15

Andrew Barron

Adaptive Annealing

 

 

Lunch (Harvard Hall 104)

 

 

Parallel Sessions

 

Sesssion A (Sever Hall 103)

Session B (Sever Hall 203)

1:00-1:40

Simon Godsill

Sequential Monte Carlo methods for tracking of partially observed jump processes

 

Christophe Andrieu

Exact Approximate Algorithms for Monte Carlo computations: the

Expected Auxiliary Variable (EAV) principle

1:40-2:20

Radford M. Neal

Short-cut MCMC: An Alternative to Adaptation

Patrick J. Wolfe

Multi-Scale MCMC Methods for Sampling from Products of Gaussian Mixtures

2:20-3:00

Antonietta Mira

Adaptive Multiple Importance Sampling (AMIS)

Yuguo Chen

A New Data Augmentation Scheme

 

3:00-3:40

Galin Jones

Fixed-Width Output Analysis for Markov Chain Monte Carlo

Radu Craiu

Randomized Quasi Monte Carlo for Markov chain Monte Carlo

Coffee Break

 

3:55-4:35

Jose H. Blanchet

Lyapunov-type Inequalities in Importance Sampling and Perfect Simulation

Faming Liang

Annealing Evolutionary Stochastic Approximation Monte Carlo for

Global Optimization

4:35-5:15

Adrian Barbu

Hierarchical Image-Motion Segmentation using Swendsen-Wang Cuts

Jinfeng Zhang

Novel Monte Carlo Methods For Protein Structure Modeling

 

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