Regularized Least Squares (RLS) algorithms have the ability to avoid over-fitting problems and to express solutions as kernel expansions. However, we observe that the current RLS ...
Background: In order to interpret the results obtained from a microarray experiment, researchers often shift focus from analysis of individual differentially expressed genes to an...
In this paper we describe a method of learning hierarchical representations for describing and recognizing gestures expressed as one and two arm movements using competitive learni...
—This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target high-resolution images based ...
Abstract. We investigate bottom-up and top-down deterministic automata on unranked trees. We show that for an appropriate definition of bottom-up deterministic automata it is poss...