In this paper we address the problem of estimating and analyzing the motion in image sequences that involve fluid phenomena. In this context standard motion estimation techniques ...
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
There is a growing wealth of data describing networks of various types, including social networks, physical networks such as transportation or communication networks, and biologic...
— We propose here an analysis of a rich dataset which gives an exhaustive and dynamic view of the exchanges processed in a running eDonkey system. We focus on correlation in term...