Algorithms for Sparsity-Constrained Optimization:
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Bibliographische Detailangaben
1. Verfasser: Bahmani, Sohail (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: 2014
Schriftenreihe:Springer Theses : Recognizing Outstanding Ph.D. Research 261
Schlagworte:
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Abstract
Beschreibung: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
Beschreibung:1 Online-Ressource (XXI, 107 p.) 13 illus., 12 illus. in color
ISBN:9783319018812
DOI:10.1007/978-3-319-01881-2