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Springer Algorithms for Sparsity-Constrained Optimization: 261 (Springer Theses, 261)

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Description

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.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
18 October 2013
Listed Since
25 July 2013

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