unconstrained optimization

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1. 1▶Lecture: Least-Squares Fitting MethodsBeginning Scientific ComputingNotes
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2. 2▶Lecture: Polynomial Fits and SplinesBeginning Scientific ComputingNotes
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3. 3▶Lecture: Data Fitting with MatlabBeginning Scientific ComputingNotes
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4. 4▶Lecture: Eigenvalues and EigenvectorsBeginning Scientific ComputingNotes
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5. 5▶Lecture: Iteration Methods for Ax-bBeginning Scientific ComputingNotes
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6. 6▶Lecture: Eigen-decompositions and IterationsBeginning Scientific ComputingNotes
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7. 7▶Lecture: Unconstrained Optimization (Derivative-Free Methods)Beginning Scientific ComputingNotes
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8. 8▶Lecture: Linear Programming and Genetic AlgorithmsBeginning Scientific ComputingNotes
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9. 9▶Lecture: Unconstrained Optimization (Derivative Methods)Beginning Scientific ComputingNotes
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10. 10▶Lecture: Higher-order Integration SchemesBeginning Scientific ComputingNotes
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11. 11▶Lecture 6. Local and global minimum. Sufficient and necessary unconstrained optimality conditionsIntroduction to OptimizationNotes
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12. 12▶Lecture 4-5: Convex sets and functionsIntroduction to OptimizationNotes
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13. 13▶Lecture 2-3: Derivatives of multivariate functions: Gradient and HessianIntroduction to OptimizationNotes
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14. 14▶Lecture 1b, Linear algebra refresh:Introduction to OptimizationNotes
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15. 15▶Lecture 1a, Introduction; Examples of unconstrained and constrained optimization problems:Introduction to OptimizationNotes
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16. 16▶Lecture 16 Conic programming 1Introduction to OptimizationNotes
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17. 17▶Lecture 15 Minimax theorem, game theory and Lagrange dualityIntroduction to OptimizationNotes
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18. 18▶Lecture 14 Lagrange multipliers and penalty function method. Augmented LagrangianIntroduction to OptimizationNotes
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19. 19▶Lecture 13. Summary of unconstrained optimization. Optimization with constraintsIntroduction to OptimizationNotes
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20. 20▶Lecture 12 Sequential subspace optimization (SESOP) method and Quasi-Newton BFGSIntroduction to OptimizationNotes
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