MM optimization algorithms / Kenneth Lange, University of California, Los Angeles, California.

Author
Lange, Kenneth [Browse]
Format
Book
Language
English
Published/​Created
Philadelphia, Pennsylvania : Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104), [2016]
Description
1 PDF (x, 223 pages).

Details

Subject(s)
Publisher
Series
Restrictions note
Restricted to subscribers or individual electronic text purchasers.
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.
System details
  • Mode of access: World Wide Web.
  • System requirements: Adobe Acrobat Reader.
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.
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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