Vivak Patel, Mohammad Jahangoshahi, Daniel Adrian Maldonado
Published 2021-04-10Version 1
Deterministic and randomized, row-action and column-action solvers have become increasingly popular owing to their simplicity, low computational and memory complexities, and ease of composition with other techniques. Indeed, such solvers can be highly tailored to the given problem structure and to the hardware platform on which the problem will be solved. However, whether such tailored solvers will converge to a solution is unclear. In this work, we provide a general set of assumptions under which such solvers are guaranteed to converge with probability one. As a result, we can provide practitioners with guidance on how to design highly tailored solvers that are also guaranteed to converge.
Convergence of adaptive finite element methods for eigenvalue problems
Order of convergence of the finite element method for the $p(x)-$Laplacian
An Adaptive Euler-Maruyama Scheme For SDEs: Convergence and Stability
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