Optimization problems

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (24)

Page 1 of 3

Stationary Points Analysis

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

Optimization Methods: Lagrange Multipliers

Covers advanced optimization methods using Lagrange multipliers to find extrema of functions subject to constraints.

Lagrange Multipliers

Discusses Lagrange multipliers for optimizing functions subject to constraints, with examples illustrating their application.

Lagrange Multipliers

Covers Lagrange multipliers for optimizing functions subject to constraints on surfaces.

Optimization Methods: Convergence and Trade-offs

Covers optimization methods, convergence guarantees, trade-offs, and variance reduction techniques in numerical optimization.

Optimization Techniques: Local and Global Extrema

Discusses optimization techniques, focusing on local and global extrema in functions.

Local Extrema of Functions

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

Primal-dual Optimization: Extra-Gradient Method

Explores the Extra-Gradient method for Primal-dual optimization, covering nonconvex-concave problems, convergence rates, and practical performance.

Differentiable Functions and Lagrange Multipliers

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

Gradient Descent Methods: Theory and Computation

Explores gradient descent methods for smooth convex and non-convex problems, covering iterative strategies, convergence rates, and challenges in optimization.