Lecture
Conjugate Gradient Method: Iterative Optimization
Description
This lecture covers the continuation of the gradient method, introduction to the conjugate gradient method, and various stopping criteria. It explains the preconditioned Richardson method, convergence properties, and the computation of new iterates. The lecture also discusses the stationary and dynamic nature of the gradient method, the computation of residuals, and the Richardson method for symmetric positive definite matrices.
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