A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Background: Classification of protein sequences is a central problem in computational biology. Currently, among computational methods discriminative kernel-based approaches provid...
The visual nature of geometry applications makes them a natural area where visualization can be an effective tool for demonstrating algorithms. In this paper we propose a new mode...
James E. Baker, Isabel F. Cruz, Giuseppe Liotta, R...
The parallelization of two applications in symmetric cryptography is considered: block ciphering and a new method based on random sampling for the selection of basic substitution ...
Vincent Danjean, Roland Gillard, Serge Guelton, Je...
Abstract. In this paper, we propose new adaptive local refinement (ALR) strategies for firstorder system least-squares (FOSLS) finite element in conjunction with algebraic multi...
J. H. Adler, Thomas A. Manteuffel, Stephen F. McCo...