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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Ontological neighbourhood

Mathematics

Analysis: Numerical analysis

Mathematical logic: Set theory

Algebra: Linear algebra

Statistics

Statistical inference: Mathematical statistics

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