A tensor approximation method based on ideal minimal residual formulations for the solution of high-dimensional problems

ESAIM: Mathematical Modelling and Numerical Analysis

Volumn 48, Issue 6, 2014, Pages 1777-1806

  Billaud Friess, M ^a   Nouy, A ^a   Zahm, O ^a  

^a UNIVERSITÉ DE NANTES   (France)

Author keywords

High dimensional problems; Low rank approximation; Minimal residual; Nonlinear approximation; Proper generalized decomposition; Stochastic partial differential equation

Indexed keywords

APPROXIMATION THEORY; GALERKIN METHODS; ITERATIVE METHODS; NONLINEAR EQUATIONS; NUMERICAL METHODS; PARTIAL DIFFERENTIAL EQUATIONS; STOCHASTIC PROGRAMMING; STOCHASTIC SYSTEMS; TENSORS;

HIGH-DIMENSIONAL PROBLEMS; LOW RANK APPROXIMATIONS; MINIMAL RESIDUAL; NONLINEAR APPROXIMATION; PROPER GENERALIZED DECOMPOSITIONS; STOCHASTIC PARTIAL DIFFERENTIAL EQUATION;

APPROXIMATION ALGORITHMS;

EID: 85006266068     PISSN: 28227840     EISSN: 28047214     Source Type: Journal    
DOI: 10.1051/m2an/2014019     Document Type: Article

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