In real world scenes, objects to be classified are usually not visible from every direction, since they are almost always positioned on some kind of opaque plane. When moving a cam...
Abstract. With the drastic increase of object trajectory data, the analysis and exploration of trajectories has become a major research focus with many applications. In particular,...
In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
It is well-known that diversity among base classifiers is crucial for constructing a strong ensemble. Most existing ensemble methods obtain diverse individual learners through res...
This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...