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Optimization 2nd ed
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| 자료유형 | 단행본 |
|---|---|
| 서명/저자사항 | Optimization/ Kenneth Lange. |
| 개인저자 | Lange, Kenneth. |
| 판사항 | 2nd ed. |
| 발행사항 | New York: Springer, c2013. |
| 형태사항 | xvii, 529 p.: ill.; 24 cm. |
| 총서사항 | Springer texts in statistics;95 |
| ISBN | 9781461458371: |
| 서지주기 | Includes bibliographical references and index. |
| 내용주기 | 1. Elementary optimization -- 2. The seven c's of analysis -- 3. The gauge integral -- 4. Differentiation -- 5. Karush-Kuhn-Tucker theory -- 6. Convexity -- 7. Block relaxation -- 8. The MM algorithm -- 9. The EM algorithm -- 10. Newton's method and scoring -- 11. Conjugate gradient and quasi-Newton -- 12. Analysis of convergence -- 13. Penalty and barrier methods -- 14. Convex calculus -- 15. Feasibility and duality -- 16. Convex minimization algorithms -- 17. The calculus of variations -- Appendix. |
| 요약 | 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. Building on students' skills in calculus and linear algebra, the text provides a rigorous exposition without undue abstraction. Its stress on statistical applications will be especially appealing to graduate students of statistics and biostatistics. The intended audience also includes students in applied mathematics, computational biology, computer science, economics, and physics who want to see rigorous mathematics combined with real applications. In this second edition, the emphasis remains on finite-dimensional optimization. New material has been added on the MM algorithm, block descent and ascent, and the calculus of variations. Convex calculus is now treated in much greater depth. Advanced topics such as the Fenchel conjugate, subdifferentials, duality, feasibility, alternating projections, projected gradient methods, exact penalty methods, and Bregman iteration will equip students with the essentials for understanding modern data mining techniques in high dimensions. |
| 일반주제명 | Mathematical optimization. |
| 분류기호 | 410 |
| 언어 | 영어 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | M0520094 | 410 L274o2 | 삼성캠퍼스/종합자료실/ | 대출가능 |
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