We study multivariate approximation for continuous functions in the average case setting. The space of d variate continuous functions is equipped with the zero mean Gaussian measu...
In this paper, we develop a spatially-variant (SV) mathematical morphology theory for gray-level signals and images in the euclidean space. The proposed theory preserves the geomet...
In this paper we present a method for reformulating the Recommender Systems problem in an Information Retrieval one. In our tests we have a dataset of users who give ratings for s...
We propose a well-founded method of ranking a pool of m trained classifiers by their suitability for the current input of n instances. It can be used when dynamically selecting a s...
Background: Classification of protein sequences is a central problem in computational biology. Currently, among computational methods discriminative kernel-based approaches provid...