Random convex programs with \(L_1\)-regularization: sparsity and generalization (Q2873845)
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scientific article; zbMATH DE number 6250858
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Random convex programs with \(L_1\)-regularization: sparsity and generalization |
scientific article; zbMATH DE number 6250858 |
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27 January 2014
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random programs
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\(L_1\)-regularization
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robustness
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sparsity
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convex optimization
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scenario optimization
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0.89530176
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0.8884469
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0.8806009
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0.8802797
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0.8790996
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0.8783747
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Random convex programs with \(L_1\)-regularization: sparsity and generalization (English)
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Random convex programs are convex optimization problems that are robust with respect to the finite number of randomly sampled instances of an uncertain variable. Random convex problems, with uncertainties in the objective function, are considered. \(L_1\)-regularization is applied to shrink the number of optimization variables. Generalization property of such regularization is demonstrated. The favorable property of the method propose is that the knowledge of the probability distribution of the involved random variables.
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