Various methods exist for reducing correlation between classifiers in a multiple classifier framework. The expectation is that the composite classifier will exhibit improved perfor...
A new approach for overcoming broken ergodicity in Markov Chain Monte Carlo (MCMC) simulations of complex systems is described. The problem of broken ergodicity is often present i...
The bootstrap has become a popular method for exploring model (structure) uncertainty. Our experiments with artificial and realworld data demonstrate that the graphs learned from...
A new decision tree learning algorithm called IDX is described. More general than existing algorithms, IDX addresses issues of decision tree quality largely overlooked in the arti...
We study the integration of functions with respect to an unknown density. Information is available as oracle calls to the integrand and to the nonnormalized density function. We ar...