๐”– Scriptorium
โœฆ   LIBER   โœฆ
๐Ÿ“

Handbook of semidefinite programming : theory, algorithms, and applications

โœ Scribed by Henry Wolkowicz; Romesh Saigal; Lieven Vandenberghe (eds.)

Publisher
Kluwer
Year
2000
Tongue
English
Leaves
682
Series
International series in operations research & management science, 27
Category
Library
โฌ‡  Acquire This Volume

No coin nor oath required. For personal study only.

โœฆ Synopsis

Introduction / Henry Wolkowicz, Ramesh Saigal and Lieven Vandenberghe -- Pt. I. Theory. Convex Analysis on Symmetric Matrices / Florian Jarre. The Geometry of Semidefinite Programming / Gabor Pataki. Duality and Optimality Conditions / Alexander Shapiro and Katya Scheinberg. Self-Dual Embeddings / Etienne de Klerk, Tamas Terlaky and Kees Roos. Robustness / Aharon Ben-Tal, Laurent El Ghaoui and Arkadi Nemirovski. Error Analysis / Zhiquan Luo and Jos Sturm -- Pt. II. Algorithms. Symmetric Cones, Potential Reduction Methods / Farid Alizadeh and Stefan Schmieta. Potential Reduction and Primal-Dual Methods / Levent Tuncel. Path-Following Methods / Renato Monteiro and Michael Todd

๐Ÿ“œ SIMILAR VOLUMES

Handbook of Semidefinite Programming - T
๐Ÿ“ Handbook of Semidefinite Programming - Theory, Algorithms, and Applications
โœ Henry Wolkowicz, Romesh Saigal, Lieven Vandenberghe ๐Ÿ“‚ Library ๐Ÿ“… 2000 ๐Ÿ› Springer ๐ŸŒ English

Semidefinite programming (SDP) is one of the most exciting and active research areas in optimization. It has and continues to attract researchers with very diverse backgrounds, including experts in convex programming, linear algebra, numerical optimization, combinatorial optimization, control theory

Handbook of Semidefinite Programming - T
๐Ÿ“ Handbook of Semidefinite Programming - Theory, Algorithms, and Applications
โœ Henry Wolkowicz, Romesh Saigal, Lieven Vandenberghe ๐Ÿ“‚ Library ๐Ÿ“… 2000 ๐Ÿ› Springer ๐ŸŒ English

Semidefinite programming (SDP) is one of the most exciting and active research areas in optimization. It has and continues to attract researchers with very diverse backgrounds, including experts in convex programming, linear algebra, numerical optimization, combinatorial optimization, control theory

Aspects of Semidefinite Programming: Int
๐Ÿ“ Aspects of Semidefinite Programming: Interior Point Algorithms and Selected Applications (Applied Optimization)
โœ E. de Klerk ๐Ÿ“‚ Library ๐Ÿ“… 2002 ๐ŸŒ English

Semidefinite programming has been described as linear programming for the year 2000. It is an exciting new branch of mathematical programming, due to important applications in control theory, combinatorial optimization and other fields. Moreover, the successful interior point algorithms for linear p

Aspects of Semidefinite Programming: Int
๐Ÿ“ Aspects of Semidefinite Programming: Interior Point Algorithms and Selected Applications
โœ Etienne de Klerk (auth.) ๐Ÿ“‚ Library ๐Ÿ“… 2004 ๐Ÿ› Springer US ๐ŸŒ English

<p>Semidefinite programming has been described as linear programming for the year 2000. It is an exciting new branch of mathematical programming, due to important applications in control theory, combinatorial optimization and other fields. Moreover, the successful interior point algorithms for linea

Aspects of Semidefinite Programming: Int
๐Ÿ“ Aspects of Semidefinite Programming: Interior Point Algorithms and Selected Applications
โœ Etienne de Klerk (auth.) ๐Ÿ“‚ Library ๐Ÿ“… 2004 ๐Ÿ› Springer US ๐ŸŒ English

<p>Semidefinite programming has been described as linear programming for the year 2000. It is an exciting new branch of mathematical programming, due to important applications in control theory, combinatorial optimization and other fields. Moreover, the successful interior point algorithms for linea

Aspects of Semidefinite Programming. Int
๐Ÿ“ Aspects of Semidefinite Programming. Interior Point Algorithms and Selected Applications
โœ E. de Klerk ๐Ÿ“‚ Library ๐Ÿ“… 2010 ๐Ÿ› Springer ๐ŸŒ English

Semidefinite programming has been described as linear programming for the year 2000. It is an exciting new branch of mathematical programming, due to important applications in control theory, combinatorial optimization and other fields. Moreover, the successful interior point algorithms for linear p