Abstract. We consider the problem of learning an unknown (overcomplete) basis from an unknown sparse linear combination. Introducing the "sparse coding neural gas" algori...
Abstract Compressed domain image retrieval is going to play an increasingly important role in the future. It allows the calculation of image features and hence content-based image ...
This work discusses the problem of generating association rules from a set of transactions in a relational database, taking performance and accuracy of found results as the essent...
In previous work on "transformed mixtures of Gaussians" and "transformed hidden Markov models", we showed how the EM algorithm in a discrete latent variable mo...
We propose a method for sequential Bayesian kernel regression. As is the case for the popular Relevance Vector Machine (RVM) [10, 11], the method automatically identifies the num...