Algorithms for Sparsity-Constrained Optimization
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 o...
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| Format: | eBook |
| Language: | English |
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Cham
Springer International Publishing
2014, 2014
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| Edition: | 1st ed. 2014 |
| Series: | Springer Theses, Recognizing Outstanding Ph.D. Research
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| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
| Summary: | 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 |
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| Physical Description: | XXI, 107 p. 13 illus., 12 illus. in color online resource |
| ISBN: | 9783319018812 |