| 書目名稱 | Optimization | | 編輯 | Kenneth Lange | | 視頻video | http://file.papertrans.cn/704/703132/703132.mp4 | | 概述 | Provides an integration of mathematical theory and development of numerical algorithms for applied optimization.Includes new chapters on calculus of variations, integration, and block relaxation.Showc | | 叢書名稱 | Springer Texts in Statistics | | 圖書封面 |  | | 描述 | .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 | | 出版日期 | Textbook 2013Latest edition | | 關鍵詞 | Convexity; Differentiation; Gauge Integral; Integration; Optimization; Statistical variance | | 版次 | 2 | | doi | https://doi.org/10.1007/978-1-4614-5838-8 | | isbn_softcover | 978-1-4899-9270-3 | | isbn_ebook | 978-1-4614-5838-8Series ISSN 1431-875X Series E-ISSN 2197-4136 | | issn_series | 1431-875X | | copyright | Springer Science+Business Media New York 2013 |
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