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• W18184313 abstract "We introduce the Group Total Variation (GTV) regularizer, a modification of Total Variation that uses the ℓ2,1 norm instead of the ℓ1 one to deal with multidimensional features. When used as the only regularizer, GTV can be applied jointly with iterative convex optimization algorithms such as FISTA. This requires to compute its proximal operator which we derive using a dual formulation. GTV can also be combined with a Group Lasso (GL) regularizer, leading to what we call Group Fused Lasso (GFL) whose proximal operator can now be computed combining the GTV and GL proximals through Dykstra algorithm. We will illustrate how to apply GFL in strongly structured but ill-posed regression problems as well as the use of GTV to denoise colour images." @default.
• W18184313 created "2016-06-24" @default.
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• W18184313 date "2013-01-01" @default.
• W18184313 modified "2023-10-12" @default.
• W18184313 title "Group Fused Lasso" @default.
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• W18184313 doi "https://doi.org/10.1007/978-3-642-40728-4_9" @default.
• W18184313 hasPublicationYear "2013" @default.
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