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Convex Analysis and Minimization Algorithms: Part 1: Fundamentals (Grundlehren der mathematischen Wissenschaften) [Hardcover]

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Item description for Convex Analysis and Minimization Algorithms: Part 1: Fundamentals (Grundlehren der mathematischen Wissenschaften) by Jean-Baptiste Hiriart-Urruty & Claude Lemarechal...

Convex Analysis may be considered as a refinement of standard calculus, with equalities and approximations replaced by inequalities. As such, it can easily be integrated into a graduate study curriculum. Minimization algorithms, more specifically those adapted to non-differentiable functions, provide an immediate application of convex analysis to various fields related to optimization and operations research. These two topics making up the title of the book, reflect the two origins of the authors, who belong respectively to the academic world and to that of applications. Part I can be used as an introductory textbook (as a basis for courses, or for self-study); Part II continues this at a higher technical level and is addressed more to specialists, collecting results that so far have not appeared in books.



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Item Specifications...


Pages   461
Est. Packaging Dimensions:   Length: 1.25" Width: 6.75" Height: 9.75"
Weight:   1.74 lbs.
Binding  Hardcover
Release Date   Oct 30, 1996
Publisher   Springer
ISBN  3540568506  
ISBN13  9783540568506  


Availability  117 units.
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More About Jean-Baptiste Hiriart-Urruty & Claude Lemarechal


Register your artisan biography and upload your photo! Hiriart-Urruty is Professor of Mathematics at Universite Paul Sabatier, Toulouse, France.

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Product Categories

1Books > Special Features > New & Used Textbooks > Sciences > Mathematics > Calculus
2Books > Subjects > Professional & Technical > Professional Science > Mathematics > Applied > General
3Books > Subjects > Professional & Technical > Professional Science > Mathematics > Applied > Linear Programming
4Books > Subjects > Professional & Technical > Professional Science > Mathematics > Pure Mathematics > Calculus
5Books > Subjects > Science > Mathematics > Applied > General
6Books > Subjects > Science > Mathematics > Applied > Linear Programming
7Books > Subjects > Science > Mathematics > General
8Books > Subjects > Science > Mathematics > Mathematical Analysis
9Books > Subjects > Science > Mathematics > Pure Mathematics > Calculus



Reviews - What do customers think about Convex Analysis and Minimization Algorithms: Part 1: Fundamentals (Grundlehren der mathematischen Wissenschaften)?

A good reference to the bundle method  Jan 27, 2001
Lemarechal and Kiwiel introduced the bundle method in the 80's as a means to optimise nonsmooth convex functions. Recently Christoph Helmberg developed a spectral bundle approach to solving semidefinite programs, by rewriting SDP's with a constant trace as eigenvalue optimisation problems. The Spectral bundle methods outperforms the traditional interior point approaches to SDP's as these methods are typically unable to handle large SDP's with a large number of constraints.

This book provides a detailed description of the bundle method for nondifferentiable optimisation. I am going to purchase a copy of this book (I already have volume one with me) and can only strongly recommend the book to anyone interested in nondifferentiable optimisation and semidefinite programming.

 

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