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Parallel sparse matrix-matrix multiplication algorithms (PSpGEMM) spend most of their running time on inter-process communication. In the case of distributed matrix-matrix multiplications, much of this time is spent on interchanging the partial results that are needed to calculate the final...
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In this paper we consider the simpler GMRES method augmented by approximate eigenvectors for solving nonsymmetric … linear systems. We modify the augmented restarted simpler GMRES proposed by Boojhawon and Bhuruth to obtain a simpler GMRES … with deflated restarting. Moreover, we also propose a residual-based simpler GMRES with deflated restarting, which is …
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The solutions of a macroeconometricmodel with expectations of future-dated variables has to be approximated by numerical simulations. A brief review of deterministic and stochastic dynamic simulations of a backward-looking model is followed by a conceptual presentation of methods for dynamic...
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We build a novel leading indicator (LI) for the EU industrial production (IP). Differently from previous studies, the technique developed in this paper is able to produce an ex-ante LI that is immune to "overlapping information drawbacks". In addition, the set of variables composing the LI...
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Many applications in data analysis rely on the decomposition of a data matrix into a low-rank and a sparse component. Existing methods that tackle this task use the nuclear norm and <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$$\ell _1$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <msub> <mi>ℓ</mi> <mn>1</mn> </msub> </math> </EquationSource> </InlineEquation>-cost functions as convex relaxations of the rank constraint and the sparsity measure,...</equationsource></equationsource></inlineequation>
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