Handbook of Semidefinite Programming: Theory, Algorithms, and Applications - Tapa blanda

Sinopsis

Contributing Authors. List of Figures. List of Tables. Preface. 1. Introduction; H. Wolkowicz, et al. Part I: Theory. 2. Convex Analysis on Symmetric Matrices; F. Jarre. 3. The Geometry of Semidefinite Programming; G. Pataki. 4. Duality and Optimality Conditions; A. Shapiro, K. Scheinberg. 5. Self-Dual Embeddings; E. de Klerk, et al. 6. Robustness; A. Ben-Tal, et al. 7. Error Analysis; Zhiquan Luo, J. Sturm. Part II: Algorithms. 8. Symmetric Cones, Potential Reduction Methods; F. Alizadeh, S. Schmieta. 9. Potential Reduction and Primal-Dual Methods; L. Tuncel. 10. Path-Following Methods; R. Monteiro, M. Todd. 11. Bundle Methods and Eigenvalue Functions; C. Helmberg, F. Oustry. Part III: Applications and Extensions. 12. Combinatorial Optimization; M. Goemans, F. Rendl. 13. Nonconvex Quadratic Optimization; Y. Nesterov, et al. 14. SDP in Systems and Control Theory; V. Balakrishnan, Fan Wang. 15. Structural Design; A. Ben-Tal, A. Nemirovski. 16. Moment Problems and Semidefinite Optimization; D. Bertsimas, J. Sethuraman. 17. Design of Experiments in Statistics; V. Fedorov, J. Lee. 18. Matrix Completion Problems; A. Alfakih, H. Wolkowicz. 19. Eigenvalue Problems and Nonconvex Minimization; F. Jarre. 20. General Nonlinear Programming; S. Kruk, H. Wolkowicz. References. Appendix A-.1. Conclusion and Further Historical Notes. A-.2.Index.

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