Algorithms for Sparsity-Constrained Optimization
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| SP SpringerNatureLink Shop INT | 103,50 GBP | free | 103,50 GBP | Disponibil | 3 zile în urmă | View offer |
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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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