Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
Abstract--We study the design of media streaming applications in the presence of multiple heterogeneous wireless access methods with different throughputs and costs. Our objective ...
The popularity of location-based services and the need to perform real-time processing on them has led to an interest in queries on road networks, such as finding shortest paths a...
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
This paper tackles an important aspect of the variational problem underlying active contours: optimization by gradient flows. Classically, the definition of a gradient depends d...
Guillaume Charpiat, Pierre Maurel, Jean-Philippe P...