Details

Subject(s)

• Mathematical optimization [Browse]
• Maxima and minima [Browse]
• Algorithms [Browse]

Publisher

• Society for Industrial and Applied Mathematics [Browse]

Series

• Other titles in applied mathematics. [More in this series]
• Other titles in applied mathematics ; 147 [More in this series]

Summary note

MM Optimization Algorithms offers an overview of the MM principle, a device for deriving optimization algorithms satisfying the ascent or descent property. These algorithms can separate the variables of a problem, avoid large matrix inversions, linearize a problem, restore symmetry, deal with equality and inequality constraints gracefully, and turn a nondifferentiable problem into a smooth problem.

Notes

Bibliographic Level Mode of Issuance: Monograph

Bibliographic references

Includes bibliographical references and index.

Source of description

Description based on title page of print version.

Language note

English

Contents

• Preface
• 1. Beginning examples
• 2. Convexity and inequalities
• 3. Nonsmooth analysis
• 4. Majorization and minorization
• 5. Proximal algorithms
• 6. Regression and multivariate analysis
• 7. Convergence and acceleration
• Appendix A. Mathematical background.

Show 6 more Contents items

Other format(s)

Also available in print version.

Other title(s)

Optimization algorithms.

ISBN

1-61197-440-2

Publisher no.

OT147

LCCN

2016018451

Statement on language in description

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