In this program
- Unconstrained optimization
- Convexity
- Gradient descent
- Newton's method for multivariable functions
- Constrained optimization: Lagrange multipliers
- Karush–Kuhn–Tucker (KKT) conditions (introduction)
- Convex sets and convex functions (definitions and examples)
Nonlinear optimization
Karush–Kuhn–Tucker (KKT) conditions (introduction)
Optimization & linear programming · STEM / applied
Topic
Karush–Kuhn–Tucker (KKT) conditions (introduction)
Undergraduate Optimization & Linear Programming — scope drawn from open optimization / LP materials (e.g. Boyd convex-optimization companion undergrad tracks) and typical US syllabi.