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...
When constructing programs to process XML documents, we immediately face the question as to how XML documents should be represented internally in the programming language we use. C...
Why do people create extra representations to help them make sense of situations, diagrams, illustrations, instructions and problems? The obvious explanation-external representatio...
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...