Lecture 10.1: the gradient method with "exact" line search
Completion requirements
Multivariate unconstrained optimization. Choice of the direction: the obvious one = steepest descent. Choice of the stepsize, the obvious one: "exact" stepsize. Convergence analysis for approximate line search to an approximate stationary point. Stopping conditions, what you would like to have, what you can have, the relationships between the two. "Real" inexact line search: Armijo-Wolfe conditions, what they mean, why they work.