Optimization
Finite-dimensional optimization problems occur throughout the mathematical sciences. The majority of these problems cannot be solved analytically. This introduction to optimization attempts to strike a balance between presentation of mathematical theory and development of numerical algorithms. Build...
Κύριος συγγραφέας: | |
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Συγγραφή απο Οργανισμό/Αρχή: | |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
New York, NY :
Springer New York : Imprint: Springer,
2013.
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Έκδοση: | 2nd ed. 2013. |
Σειρά: | Springer Texts in Statistics,
95 |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Elementary Optimization
- The Seven C’s of Analysis
- The Gauge Integral
- Differentiation
- Karush-Kuhn-Tucker Theory
- Convexity
- Block Relaxation
- The MM Algorithm
- The EM Algorithm
- Newton’s Method and Scoring
- Conjugate Gradient and Quasi-Newton
- Analysis of Convergence
- Penalty and Barrier Methods
- Convex Calculus
- Feasibility and Duality
- Convex Minimization Algorithms
- The Calculus of Variations
- Appendix: Mathematical Notes
- References
- Index.