We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
We propose a novel, computationally efficient generative topographic model for inferring low dimensional representations of high dimensional data sets, designed to exploit data s...
Stochastic simulations and other scientific applications that depend on random numbers are increasingly implemented in a parallelized manner in programmable logic. High-quality ps...
Some combinatorial generation problems can be broken into subproblems for which loopless algorithms already exist. We discuss means by which loopless algorithms can be fused to pr...
An unstructured tetrahedral mesh generation algorithm for 3D model with constraints is presented. To automatically generate a tetrahedral mesh for model with constraints, an advan...