Supervised learning techniques for text classi cation often require a large number of labeled examples to learn accurately. One way to reduce the amountoflabeled datarequired is t...
This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...
In this paper, we introduce a novel binary method for fast computation of an objective function to measure inter and intra class similarities, which is used for combining multiple...
In this paper we develop a system for human behaviour recognition in video sequences. Human behaviour is modelled as a stochastic sequence of actions. Actions are described by a f...
We propose a new discontinuous Galerkin (DG) method based on [9] to solve a class of Hamilton-Jacobi equations that arises from optimal control problems. These equations are connec...