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Lecture
Minimization of functions
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Related lectures (29)
Local Extrema of Functions
Discusses local extrema of functions in two variables around the point (0,0).
Morse Theory: Critical Points and Non-Degeneracy
Covers Morse theory, focusing on critical points and non-degeneracy.
Taylor's Formula: Developments and Extrema
Covers Taylor's formula, developments, and extrema of functions, discussing convexity and concavity.
Bernoulli's Hospital Rule
MOOC: Analysis I
MOOC: Analysis I (part 6) : Study of functions, limited developments
Covers the statement of the Bernoulli's Hospital Rule and its application.
Integral Techniques: Integration by Parts
Explores the integration by parts technique through examples, showcasing its step-by-step application to functions like cos(x) and sin(x.
Mathematics: Functions and Series
Explores functions, series, and critical points in mathematics, including maximum, minimum, supremum, and infimum concepts.
Applications of Theorems
Demonstrates the practical application of theorems in calculus through two clever examples.
Taylor Polynomial: Order 2
Presents the solution to finding the second-order Taylor polynomial of a function.
Optimization: Local Extrema
Explains how to find local extrema of functions using derivatives and critical points.
Linear Algebra: Injective Functions
Explores injective functions in linear algebra, demonstrating how to prove injectivity step by step.
Volume Calculation: Spheres and Loops
Explores volume calculation for spheres, function definition, and loop logic.
Basic Notions
MOOC: Analysis I (part 1): Prelude, basic concepts, real numbers
MOOC: Analysis I
Covers the basic concepts of sets, functions, and number systems.
Optimization Methods: Lagrange Multipliers
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Covers advanced optimization methods using Lagrange multipliers to find extrema of functions subject to constraints.
Optimization: Extrema of Functions
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Covers the optimization of functions, focusing on finding the maximum and minimum values.
Optimization Techniques: Local and Global Extrema
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Discusses optimization techniques, focusing on local and global extrema in functions.
Implicit Functions Theorem
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Covers the Implicit Functions Theorem, explaining how equations can define functions implicitly.
Differentiable Functions and Lagrange Multipliers
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Covers differentiable functions, extreme points, and the Lagrange multiplier method for optimization.
Limits and Continuity: Analysis 1
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Explores limits, continuity, and uniform continuity in functions, including properties at specific points and closed intervals.
Convex Functions
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Covers the properties and operations of convex functions.
Implicit Functions Theorem
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Covers the Implicit Functions Theorem, providing a general understanding of implicit functions.
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