Much recent research in decision theoretic planning has adopted Markov decision processes (MDPs) as the model of choice, and has attempted to make their solution more tractable by...
The problem of building a regression tree is considered when the response variable is a probability density function. Splitting criteria which are well adapted to measure the diss...
We present a new sparse Gaussian Process (GP) model for regression. The key novel idea is to sparsify the spectral representation of the GP. This leads to a simple, practical algo...
—Symmetry reduction is a technique for combating state-space explosion in model checking. The generic representatives approach to symmetry reduction uses a language-level transla...
A logistic regression classification algorithm is developed for problems in which the feature vectors may be missing data (features). Single or multiple imputation for the missing...
David Williams, Xuejun Liao, Ya Xue, Lawrence Cari...