The Transhipment Problem: Optimality Conditions

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Optimization with Constraints: KKT Conditions

Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.

Primal-dual Optimization: Extra-Gradient Method

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

Distributionally Robust Portfolio Optimization

Explores distributionally robust portfolio optimization and compares different estimation approaches and methods for portfolio evaluation.

Convex Optimization: Introduction and Sets

Covers the fundamentals of convex optimization, including mathematical problems, minimizers, and solution concepts, with an emphasis on efficient methods and practical applications.

KKT for convex problems and Slater's CQ

Covers the KKT conditions and Slater's condition in convex optimization problems.

Optimization Methods in Machine Learning

Explores optimization methods in machine learning, emphasizing gradients, costs, and computational efforts for efficient model training.

Optimal Control: OCPs

Covers Optimal Control Problems focusing on necessary conditions, existence of optimal controls, and numerical solutions.

Equivalent formulation

Covers the concept of equivalent formulation in constrained optimization and explores the tangent cone.

Optimization Framework: Inequality Constraints

Covers an optimization framework with inequality constraints and Karush-Kahn Tucker conditions.

Convex Optimization: Exercises

Covers exercises on convex optimization, focusing on formulating and solving optimization problems using YALMIP and solvers like GUROBI and MOSEK.