lecture method conjugate

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1. 1▶Lecture 6. Local and global minimum. Sufficient and necessary unconstrained optimality conditionsIntroduction to OptimizationNotes
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2. 2▶Lecture 4-5: Convex sets and functionsIntroduction to OptimizationNotes
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3. 3▶Lecture 2-3: Derivatives of multivariate functions: Gradient and HessianIntroduction to OptimizationNotes
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4. 4▶Lecture 1b, Linear algebra refresh:Introduction to OptimizationNotes
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5. 5▶Lecture 1a, Introduction; Examples of unconstrained and constrained optimization problems:Introduction to OptimizationNotes
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6. 6▶Lecture 16 Conic programming 1Introduction to OptimizationNotes
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7. 7▶Lecture 15 Minimax theorem, game theory and Lagrange dualityIntroduction to OptimizationNotes
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8. 8▶Lecture 14 Lagrange multipliers and penalty function method. Augmented LagrangianIntroduction to OptimizationNotes
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9. 9▶Lecture 13. Summary of unconstrained optimization. Optimization with constraintsIntroduction to OptimizationNotes
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10. 10▶Lecture 12 Sequential subspace optimization (SESOP) method and Quasi-Newton BFGSIntroduction to OptimizationNotes
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