MM Optimization Algorithms (Hardcover)
Language: English
Published by Society for Industrial & Applied Mathematics,U.S., New York, 2016
- Hardcover
- New
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
AbeBooks seller since June 22, 2007
Condition: New
£ 129.69
Quantity: 1 available
Add to basketItem description from seller
Hardcover. 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. Turn a non-differentiable 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.Summarizes a large amount of literature that has not reached book form before. Presents the first extended treatment of MM algorithms, which are ideal for high-dimensional optimization problems in data mining, imaging, and genomics. The author derives numerous algorithms from a broad diversity of application areas, with a particular emphasis on statistics, biology, and data mining. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…
Seller Inventory # 9781611974393
- Title
- MM Optimization Algorithms (Hardcover)
- Author
- Kenneth Lange
- Publisher
- Society for Industrial & Applied Mathematics,U.S., New York
- Publication year
- 2016
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1611974399
- ISBN 13
- 9781611974393
- Separate the variables of a problem.
- Avoid large matrix inversions.
- Linearize a problem.
- Restore symmetry.
- Deal with equality and inequality constraints gracefully.
- Turn a non-differentiable 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.
- Summarizes a large amount of literature that has not reached book form before.
-
-
"Synopsis" may belong to another edition of this title.
AussieBookSeller
Truganina, VIC, Australia
AbeBooks seller since June 22, 2007
Shipping rates from Australia to U.S.A.
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The Nile Group Pty Ltd
42 Apex Drive
Truganina, VIC Australia 3029
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