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Image of Algorithms for Sparsity-Constrained Optimization

Electronic Resource

Algorithms for Sparsity-Constrained Optimization

Bahmani, Sohail - Personal Name;

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This thesis demonstrates techniques that provide faster and more accurate solutions to a variety of problems in machine learning and signal processing. The author proposes a "greedy" algorithm, deriving sparse solutions with guarantees of optimality. The use of this algorithm removes many of the inaccuracies that occurred with the use of previous models.


Availability
Inventory Code Barcode Call Number Location Status
1408000504EB0001603519.6 Bah aCentral Library (OPAC)Available
Detail Information
Series Title
Springer Theses
Call Number
519.6 Bah a
Publisher
Switzerland : Springer Cham., 2013
Collation
xxi, 107p.: Ill.
Language
English
ISBN/ISSN
978-3-319-01881-2
Classification
519.6
Content Type
-
Media Type
-
Carrier Type
-
Edition
1
Subject(s)
Mathematical optimization
Specific Detail Info
-
Statement of Responsibility
RIZAL
Other version/related

No other version available

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  • Algorithms for Sparsity-Constrained Optimization
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