Convex Optimization pdf epub mobi txt 电子书下载 2025

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出版者:Cambridge University Press

作者:Stephen Boyd

出品人:

页数:727

译者:

出版时间:2004-3-8

价格:USD 90.00

装帧:Hardcover

isbn号码:9780521833783

丛书系列:

图书标签:

数学
optimization
机器学习
优化
ConvexOptimization
convex
Mathematics
Optimization
凸优化
数学规划
最优化理论
运筹学
线性代数
算法设计
机器学习
工程数学
非线性规划
应用数学

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具体描述

Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.

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”初版即过时“ 这本书是相当尴尬的，记得英文是04年出的， 05-06年以后，这方面的求解方法大量涌现，尤其是关于L1 L2范数的优化文章压缩感知、sparse model在计算机视觉等领域的火热直接推动了 L-p 范数优化的广泛研究内点法(本书主要方法) 被当作 base method 来比...

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Copyright in this book is held by Cambridge University Press, who have kindly agreed to allow us to keep the book available on the web. http://www.stanford.edu/~boyd/cvxbook/ you will find e-book and the exercises answer book. Cheers --- All the conte...

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扫码关注公众号「图灵的猫」，点击“学习资料”菜单，可以获得海量python、机器学习、深度学习书籍、课程资源，以及书中对应习题答案和代码。后台回复SSR更有机场节点相送~ 我总结了深度学习、机器学习领域中所有会用到的数学知识，大家在制定计划时可以以这些知识点为脉络进...

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这本书主要是面向实际应用。书中提供了凸优化的理论框架，但不强调复杂的定理证明。丰富的实例是这本书的特色。实例涉及的领域非常广例如通信，金融，机器学习等等。 Stephen教授在个人主页上提供了免费电子版本，而且还包含了习题以及相关数据和程序的下载。课程的讲义也可...

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强大的数学工具----凸优化！用于解决很多工程问题无数科学研究者在这上面砸无数文章这本书是对凸优化最全面的介绍但是阅读前最好有较好的矩阵论运算的基础比如向量分解，特征值分解等等学完此书再看些文章可以感觉你真正学到了东西！！