MM optimization algorithms
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.
Read More ↓Title Statements
- Full title :MM optimization algorithms / Kenneth Lange.
Summary
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.
Read More ↓Edition Statements
- Publication Date:2016
Publication Statements
- Publisher(s):Society for Industrial and Applied Mathematics
- Place of Publication:Philadelphia
- Language:eng
- Publication Date:2016
The Physical Object
- Description:1 online resource
Edition Identifiers
- ISBN:9781611974409, 1611974402
- oclc:ocn948669753
- LC Classification:QA402.5
- Dewey Decimal:519.6
Table of 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.
Read More ↓Subjects
Writers
More from this Series
No reviews yet. Be the first to rate this work.
Related Works
more →
Mining sequential patterns from large data sets
Optimization algorithms in physics
Rate & Review