Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Low-rank approximations which are computed from selected rows and columns of a given data matrix have attracted considerable attention lately. They have been proposed as an altern...
Christian Thurau, Kristian Kersting, Christian Bau...
We describe an approach for acquiring the domain-specific dialog knowledge required to configure a task-oriented dialog system that uses human-human interaction data. The key aspe...
To be efficient, data protection algorithms should generally exploit the properties of the media information in the transform domain. In this paper, we will advocate the use of no...
Philippe Jost, Pierre Vandergheynst, Pascal Frossa...
We present a variational framework for determination of intra-voxel fiber orientations from High Angular Resolution Diffusion-Weighted (HARD) MRI under the assumption of biGaussia...