Descent methods and line search: Second Wolfe condition

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Covers optimization techniques and their application in solving real-world problems.

Introduces the First Wolfe condition to ensure a proportional decrease in the objective function relative to the step length.

Covers directional derivative, differentiability, and gradient matrices, emphasizing the first order.

Covers directional derivatives, implicit functions, and the concept of the maximum.

Explores the role of first and second derivatives in function curvature and convexity.

Covers the definition of directional derivative and provides illustrative examples.

Explores gradient in scalar fields, directional derivatives, and level sets.

Discusses the solution to a mock exam problem on adversarial training and the uniqueness of solutions.

Explores tangent planes, implicit functions, and directional derivatives in relation to graphs of functions.

Covers the concept and calculation of directional derivatives in multivariable calculus.