Algorithms for Sparsity-Constrained Optimization - Sohail Bahmani
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Piegāde 17-23 darba dienu laikā
30 dienu atgriešanas politika
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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Aprašymas
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.
Vairāk informācijas
| Autors | Sohail Bahmani |
|---|---|
| Izdevējs | Springer International Publishing |
| Series | Springer Theses |
| Izlaides gads | 2013 |
| Vāka tips | Cietais vāks |
| EAN | 9783319018805 |