We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
Sparse representation for machine learning has been exploited in past years. Several sparse representation based classification algorithms have been developed for some application...
Visual tracking is one of the central problems in computer vision. A crucial problem of tracking is how to represent the object. Traditional appearance-based trackers are using inc...
Procedural representations of control policies have two advantages when facing the scale-up problem in learning tasks. First they are implicit, with potential for inductive genera...
An approach of employing Information Visualisation to develop systems that facilitate instructors in web-based distance learning is presented here. The paper describes a tool, cal...