We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
In this paper we propose an efficient algorithm for reducing a large mixture of Gaussians into a smaller mixture while still preserving the component structure of the original mod...
This paper focuses on the discovery of surprising, unexpected patterns, based on a data mining method that consists of detecting instances of Simpson's paradox. By its very n...
We present a novel algorithm for rendering physically-based soft shadows in complex scenes. Instead of casting shadow rays, we place both the points to be shaded and the samples o...