Introduces Dynamic Programming, focusing on saving computation by remembering previous calculations and applying it to solve optimization problems efficiently.
Explores KKT conditions in convex optimization, covering dual problems, logarithmic constraints, least squares, matrix functions, and suboptimality of covering ellipsoids.
