Fermat's theorem (stationary points)

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Related lectures (30)

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Analyse II: Stationary Points Classification

Covers the classification of stationary points in functions of two variables using the Hessian matrix.

Stationary Points Analysis

Covers the analysis of stationary points in functions, focusing on optimization methods.

Implicit Function Theorem: Local Extrema

Explores the Implicit Function Theorem, local extrema, supporting hyperplanes, and higher-order derivatives.

Nature of Extremum Points

Covers the nature of extremum points and their classification as stationary or saddle points.

Implicit Function Theorem

Explores the Implicit Function Theorem, supporting hyperplanes, local extrema, and higher-order derivatives, concluding with the classification of stationary points.

Optimization with Inequalities

Explores optimization with inequality constraints, emphasizing finding extreme values and stationary points.

Derivatives and Reciprocal Functions

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

Global Extrema of Functions in R^2

Explores global extrema of functions in R^2, discussing methods to find maximum and minimum points.

Local Extremums of Functions

Explains local and absolute extremums of functions and the classification of critical points.

Composite Convex Minimization

Covers solution methods for composite convex minimization and explores examples like ₁-regularized least squares and phase retrieval.