Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
R package flexmix provides flexible modelling of finite mixtures of regression models using the EM algorithm. Several new features of the software such as fixed and nested var...
We extend the Gaussian scale mixture model of dependent subspace source densities to include non-radially symmetric densities using Generalized Gaussian random variables linked by ...
Jason A. Palmer, Kenneth Kreutz-Delgado, Bhaskar D...
Background: The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding pro...
Ross K. Shepherd, Theo H. E. Meuwissen, John A. Wo...
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...