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...
| Κύριος συγγραφέας: | |
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| Συγγραφή απο Οργανισμό/Αρχή: | |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2014.
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| Σειρά: | Springer Theses, Recognizing Outstanding Ph.D. Research,
261 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
| Περίληψη: | 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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| Φυσική περιγραφή: | XXI, 107 p. 13 illus., 12 illus. in color. online resource. |
| ISBN: | 9783319018812 |
| ISSN: | 2190-5053 ; |
