Algorithms for Sparsity-Constrained Optimization - Sohail Bahmani
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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.
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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.
Daugiau informacijos
| Autorius | Sohail Bahmani |
|---|---|
| Leidėjas | Springer Nature Switzerland |
| Series | Springer Theses |
| Išleidimo metai | 2016 |
| Viršelio tipas | Minkšti viršeliai |
| EAN | 9783319377193 |