An Introduction to MCMC for Machine Learning
EM, MCMC, and Chain Flipping for Structure from Motion with Unknown Correspondence
Mixtures of Factor Analysers. Bayesian Estimation and Inference by Stochastic Simulation
Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks
Improving Markov Chain Monte Carlo Model Search for Data Mining
Classification with Bayesian MARS
Population Markov Chain Monte Carlo
A Noninformative Prior for Neural Networks
Introduction
Combining Classifiers with Meta Decision Trees
Ranking Learning Algorithms: Using IBL and Meta-Learning on Accuracy and Time Results
Learning to Match the Schemas of Data Sources: A Multistrategy Approach
Clustered Partial Linear Regression
Complete Mining of Frequent Patterns from Graphs: Mining Graph Data