Optimization Techniques: Local and Global Extrema

Related lectures (18)

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Covers differentiable functions, extreme points, and the Lagrange multiplier method for optimization.

Covers the conditions for finding absolute extrema in multivariable functions.

Covers Taylor's formula, developments, and extrema of functions, discussing convexity and concavity.

Covers the optimization of functions, focusing on finding the maximum and minimum values over a given domain.

Covers the differentiability of functions of multiple variables and the significance of directional derivatives and gradients.

Discusses limits of multivariable functions, focusing on definitions, examples, and techniques for calculating limits effectively.

Discusses local extrema of functions in two variables around the point (0,0).

Covers derivatives, reciprocal functions, Rolle's theorem, and extremum local concepts.

Demonstrates the practical application of theorems in calculus through two clever examples.

Explains how to find local extrema of functions using derivatives and critical points.