Gradient descent and fast artificial time integration

DOI10.1051/m2an/2009025zbMath1169.65329OpenAlexW2144294838MaRDI QIDQ5192617

Hui Huang, Kees van den Doel, Benar Fux Svaiter, Uri M. Ascher

Publication date: 6 August 2009

Published in: ESAIM: Mathematical Modelling and Numerical Analysis (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/194470

zbMATH Keywords

absolute stabilityfinite volume methodregularizationnumerical examplesinitial value problemssteady stategradient descentforward Eulerartificial timeGreedy algorithmslagged steepest descent

Mathematics Subject Classification ID

Computational methods for sparse matrices (65F50) Finite difference methods for initial value and initial-boundary value problems involving PDEs (65M06) Iterative numerical methods for linear systems (65F10) Initial value problems for second-order parabolic equations (35K15)

Related Items (13)

On the regularizing behavior of the SDA and SDC gradient methods in the solution of linear ill-posed problems ⋮ A vector regularization method to solve linear inverse problems ⋮ Runge-Kutta-like scaling techniques for first-order methods in convex optimization ⋮ Cooperative concurrent asynchronous computation of the solution of symmetric linear systems ⋮ Delayed Gradient Methods for Symmetric and Positive Definite Linear Systems ⋮ Adaptive POD-DEIM correction for Turing pattern approximation in reaction-diffusion PDE systems ⋮ Fast gradient methods with alignment for symmetric linear systems without using Cauchy step ⋮ The chaotic nature of faster gradient descent methods ⋮ Adaptive choice of the Tikhonov regularization parameter to solve ill-posed linear algebraic equations via Liapunov optimizing control ⋮ A dynamical systems framework for intermittent data assimilation ⋮ Faster gradient descent and the efficient recovery of images ⋮ Matrix forms of iterative algorithms to solve large-scale discrete ill-posed problems with an application to image restoration ⋮ An optimal tri-vector iterative algorithm for solving ill-posed linear inverse problems

Uses Software

• RODAS
• SPGL1

Cites Work

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