Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
—In this paper, we investigate data parallelism in exact inference with respect to arbitrary junction trees. Exact inference is a key problem in exploring probabilistic graphical...
The objective of this paper is to extend, in the context of multicore architectures, the concepts of tile algorithms [Buttari et al., 2007] for Cholesky, LU, QR factorizations to t...
Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
This paper introduces a region-of-interest visual hull refinement technique, based on flexible voxel grids for volumetric visual hull reconstructions. Region-of-interest refinemen...