MM optimization algorithms

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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.

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Title Statements

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

Summary

Edition Statements

Publication Date:2016

Publication Statements

Publisher(s):Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104)
Place of Publication:Philadelphia, Pennsylvania
Language:eng
Publication Date:2016

Notes

Titre de l'écran-tire (visionné le 16 août 2016).

The Physical Object

Description:1 ressource en ligne (x, 223 pages) : : bfichiers PDF

Edition Identifiers

ISBN:9781611974409, 1611974402
oclc:ocn956757671
LC Classification:QA402.5
Dewey Decimal:519.6

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.

Subjects

Algorithmes ALGORITHMS Computer algorithms e-books Livres numériques Mathematical optimization Maxima and minima Maximums et minimums Optimisation mathématique