Optimization models
Book information
Description
Content: 1. Introduction Part I. Linear Algebra: 2. Vectors 3. Matrices 4. Symmetric matrices 5. Singular value decomposition 6. Linear equations and least-squares 7. Matrix algorithms Part II. Convex Optimization: 8. Convexity 9. Linear, quadratic and geometric models 10. Second-order cone and robust models 11. Semidefinite models 12. Introduction to algorithms Part III. Applications: 13. Learning from data 14. Computational finance 15. Control problems 16. Engineering design.
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