Bayesian belief propagation in graphical models has been recently shown to have very close ties to inference methods based in statistical physics. After Yedidia et al. demonstrate...
Protein dispensability is fundamental to understanding of gene function and evolution. It is usually studied at the individual gene phenotype level. Recent advances in generating ...
A new approach to the Text Categorization problem is here presented. It is called Gaussian Weighting and it is a supervised learning algorithm that, during the training phase, est...
Adaptive mesh refinement (AMR) is a numerical simulation technique used in computational fluid dynamics (CFD). By using a set of nested grids of different resolutions, AMR combine...
Gunther H. Weber, Oliver Kreylos, Terry J. Ligocki...
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...