Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
In this paper, we address the problem of segmenting data defined on a manifold into a set of regions with uniform properties. In particular, we propose a numerical method when the ...
Inferring 3D body pose as well as viewpoint from a single silhouette image is a challenging problem. We present a new generative model to represent shape deformations according to...
Abstract. Most of the approaches dedicated to fiber tracking from diffusionweighted MR data rely on a tensor model. However, the tensor model can only resolve a single fiber orient...
Most up-to-date well-behaved topic-based summarization systems are built upon the extractive framework. They score the sentences based on the associated features by manually assig...