Convex Optimization Theory/ Dimitri P Bertsekas
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TextPublication details: Andhra Pradesh: Universities Press (India) Private Limited, 2010. Description: xii,407pISBN: 9788173717147DDC classification: 519.7 Summary: An insightful, concise, and rigorous treatment of the basic theory of convex sets and functions in finite dimensions, and the analytical/geometrical foundations of convex optimization and duality theory. Convexity theory is first developed in a simple accessible manner, using easily visualized proofs. Then the focus shifts to a transparent geometrical line of analysis to develop the fundamental duality between descriptions of convex sets and functions in terms of points and in terms of hyperplanes. Finally, convexity theory and abstract duality are applied to problems of constrained optimization, Fenchel and conic duality, and game theory to develop the sharpest possible duality results within a highly visual geometric framework.
| Item type | Current library | Collection | Shelving location | Call number | Materials specified | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|---|
| Books | TIFR CAM Library | NBHM | GENERAL | 519.7 BER (Browse shelf(Opens below)) | Available | M12285 |
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| 510 JOS Indian Mathematics: Engaging with the World from Ancient to Modern Times | 519.7 BER Convex Optimization Theory/ |
An insightful, concise, and rigorous treatment of the basic theory of convex sets and functions in finite dimensions, and the analytical/geometrical foundations of convex optimization and duality theory. Convexity theory is first developed in a simple accessible manner, using easily visualized proofs. Then the focus shifts to a transparent geometrical line of analysis to develop the fundamental duality between descriptions of convex sets and functions in terms of points and in terms of hyperplanes. Finally, convexity theory and abstract duality are applied to problems of constrained optimization, Fenchel and conic duality, and game theory to develop the sharpest possible duality results within a highly visual geometric framework.
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