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MOC
2010
13 years 5 days ago
H(div) preconditioning for a mixed finite element formulation of the diffusion problem with random data
We study H(div) preconditioning for the saddle-point systems that arise in a stochastic Galerkin mixed formulation of the steady-state diffusion problem with random data. The key i...
Howard C. Elman, Darran G. Furnival, Catherine E. ...
COMPUTING
2008
174views more  COMPUTING 2008»
13 years 5 months ago
Multilevel algorithms for Rannacher-Turek finite element approximation of 3D elliptic problems
Generalizing the approach of a previous work [15] the authors present multilevel preconditioners for three-dimensional (3D) elliptic problems discretized by a family of Rannacher ...
Ivan Georgiev, Johannes Kraus, Svetozar Margenov
ICML
1996
IEEE
13 years 9 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
JSCIC
2010
97views more  JSCIC 2010»
13 years 5 days ago
Finite Element Characteristic Methods Requiring no Quadrature
The characteristic methods are known to be very efficient for convection-diffusion problems including the Navier-Stokes equations. Convergence is established when the integrals ar...
Olivier Pironneau
SIAMNUM
2010
140views more  SIAMNUM 2010»
13 years 4 days ago
Finite Element Approximation of the Linear Stochastic Wave Equation with Additive Noise
Semidiscrete finite element approximation of the linear stochastic wave equation with additive noise is studied in a semigroup framework. Optimal error estimates for the determinis...
Mihály Kovács, Stig Larsson, Fardin ...