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www.ethanepperly.com | ||
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nhigham.com
Backward error is a measure of error associated with an approximate solution to a problem. Whereas the forward error is the distance between the approximate and true solutions, the backward error is how much the data must be perturbed to produce the approximate solution. For a function $latex f$ from $latex \mathbb{R}^n$ to $latex \mathbb{R}^n$ |
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nla-group.org
by Sven Hammarling and Nick Higham It is often thought that Jim Wilkinson developed backward error analysis because of his early involvement in solving systems of linear equations. In his 1970 Turing lecture [5] he described an experience, during world war II at the Armament Research Department, of solving a system of twelve linear equations |
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www.aleksandrhovhannisyan.com
Some systems of equations do not have a unique solution, but we can find an approximate solution using the method of least squares. Applications of this method include linear and polynomial regression. |
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fa.bianp.net
The Langevin algorithm is a simple and powerful method to sample from a probability distribution. It's a key ingredient of some machine learning methods such as diffusion models and differentially private learning. In this post, I'll derive a simple convergence analysis of this method in the special case when the ... |
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