Optimization with Sparsity-Inducing Penalties
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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...
Format:Paperback
Language:English
ISBN:160198510X
ISBN13:9781601985101
Release Date:January 2012
Publisher:Now Publishers
Length:124 Pages
Weight:0.41 lbs.
Dimensions:0.3" x 6.1" x 9.2"
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