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Cited article:
Uri M. Ascher, Kees van den Doel, Hui Huang, Benar F. Svaiter
ESAIM: M2AN, 43 4 (2009) 689-708
Published online: 2009-07-08
This article has been cited by the following article(s):
The Chaotic Nature of Faster Gradient Descent Methods
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Journal of Computational and Applied Mathematics 279 123 (2015)
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Runge–Kutta-like scaling techniques for first-order methods in convex optimization
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An optimal tri-vector iterative algorithm for solving ill-posed linear inverse problems
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Journal of Computational and Applied Mathematics 302 81 (2016)
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Cooperative concurrent asynchronous computation of the solution of symmetric linear systems
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Numerical Algorithms 75 (3) 587 (2017)
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A dynamical systems framework for intermittent data assimilation
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Faster Gradient Descent and the Efficient Recovery of Images
Hui Huang and Uri Ascher
Vietnam Journal of Mathematics 42 (1) 115 (2014)
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Optimal estimation of $\ell_1$-regularization prior from a regularized empirical Bayesian risk standpoint
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A vector regularization method to solve linear inverse problems
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Uri Ascher and Kees van den Doel
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Amit Bhaya, Pierre-Alexandre Bliman and Fernando Pazos
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Amit Bhaya and Fernando A. Pazos
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Matrix forms of iterative algorithms to solve large-scale discrete ill-posed problems with an application to image restoration
Fernando Pazos and Amit Bhaya
Journal of Applied Mathematics and Computing 60 (1-2) 113 (2019)
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Fast gradient methods with alignment for symmetric linear systems without using Cauchy step
Qinmeng Zou and Frédéric Magoulès
Journal of Computational and Applied Mathematics 381 113033 (2021)
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