[PDF.54os] Optimization with Sparsity-Inducing Penalties (Foundations and Trends(r) in Machine Learning)

Optimization with Sparsity-Inducing Penalties (Foundations and Trends(r) in Machine Learning)

[PDF.cy32] Optimization with Sparsity-Inducing Penalties (Foundations and Trends(r) in Machine Learning)

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 | #5278095 in Books |  Now Publishers Inc |  2011-12-23 | Original language:English | PDF # 1 |  9.21 x.26 x6.14l,.41 | File type: PDF | 124 pages

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Sparse estimation methods are aimed at using or obtaining parsimonious representations of data or models. They were first dedicated to linear variable selection but numerous extensions have now emerged such as structured sparsity or kernel selection. It turns out that many of the related estimation problems can be cast as convex optimization problems by regularizing the empirical risk with appropriate nonsmooth norms. Optimization with Sparsity-Inducing Penalties presen...

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