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MM Optimization Algorithms
Kenneth Lange
出版
SIAM
, 2016-07-11
主題
Mathematics / Optimization
Mathematics / Algebra / Linear
Mathematics / Probability & Statistics / General
Computers / Software Development & Engineering / Computer Graphics
Computers / Artificial Intelligence / Computer Vision & Pattern Recognition
Science / Physics / Mathematical & Computational
Language Arts & Disciplines / Library & Information Science / General
Computers / Data Science / Data Analytics
ISBN
1611974402
9781611974409
URL
http://books.google.com.hk/books?id=d9uuDAAAQBAJ&hl=&source=gbs_api
EBook
SAMPLE
註釋
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.
The author presents the first extended treatment of MM algorithms, which are ideal for high-dimensional optimization problems in data mining, imaging, and genomics; derives numerous algorithms from a broad diversity of application areas, with a particular emphasis on statistics, biology, and data mining; and summarizes a large amount of literature that has not reached book form before.