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Covers the basics of optimization, including historical perspectives, mathematical formulations, and practical applications in decision-making problems.
Explores KKT conditions in convex optimization, covering dual problems, logarithmic constraints, least squares, matrix functions, and suboptimality of covering ellipsoids.
