Scenario optimization

Formal sciences
Theoretical computer science
Algorithms and data structures
Combinatorial optimization

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Related lectures (29)

Optimization and Simulation

Explores optimization, simulation, heuristics, and Pareto solutions in multi-objective problems.

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Covers the basics of optimization modeling using AMPLIDE.

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Covers the KKT conditions and convex optimization, discussing constraint qualifications and tangent cones of convex sets.

Optimization Techniques

Covers optimization techniques, quizzes, and grade exercises in mathematical applications.

Robust Optimization: Polynomial Approximation & Uncertainty Sets

Explores robust optimization through polynomial approximation and uncertainty sets, including robust linear programs and optimization tricks.

Projection Matrices: Min-Cut and Gradient Descent

Explores projection matrices in the context of min-cut and gradient descent algorithms, emphasizing their role in optimization.

Projected Gradient Descent

Explores convex constrained optimization through Projected Gradient Descent, focusing on tangent space and iterative minimization.

Proximal Operators and Constrained Optimization

Introduces proximal operators, gradient methods, and constrained optimization, exploring their convergence and practical applications.

Primal-dual Optimization II

Explores primal-dual optimization methods, focusing on Lagrangian approaches and various methods like penalty, augmented Lagrangian, and splitting techniques.

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